From 3b4d350a55498519a85a68094acf0d9be9f023a9 Mon Sep 17 00:00:00 2001 From: William Cohen Date: Fri, 27 Sep 2024 12:01:39 -0400 Subject: [PATCH] rebuild pubs --- pubgen/pubs.json | 26 +++++++++- pubs-a.html | 6 ++- pubs-g.html | 120 +++-------------------------------------------- pubs-r.html | 46 +++++++++++------- pubs-s.html | 6 ++- pubs.html | 6 ++- 6 files changed, 76 insertions(+), 134 deletions(-) diff --git a/pubgen/pubs.json b/pubgen/pubs.json index 83d813c..7ec4a41 100644 --- a/pubgen/pubs.json +++ b/pubgen/pubs.json @@ -1,4 +1,16 @@ [ + { + "title": "Watch Your Steps: Observable and Modular Chains of Thought", + "authors": "Cassandra A. Cohen, William W. Cohen", + "venues": "", + "year": "2024", + "topics": "a", + "url": "https://arxiv.org/abs/2409.15359", + "cite": "preparation", + "thread": "", + "doi": "recent.html", + "comment": "" + }, { "title": "Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation", "authors": "Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson and William W. Cohen", @@ -6,7 +18,19 @@ "year": "2024", "topics": "a", "url": "https://arxiv.org/abs/2406.04291", - "cite": "progress", + "cite": "NeurIPS-2024", + "thread": "", + "doi": "recent.html", + "comment": "" + }, + { + "title": "ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights", + "authors": "Gabriel Sarch, Lawrence Jang, Michael J. Tarr, William W. Cohen, Kenneth Marino, Katerina Fragkiadaki", + "venues": "", + "year": "2024", + "topics": "a", + "url": "https://arxiv.org/abs/2406.14596", + "cite": "NeurIPS-2024", "thread": "", "doi": "recent.html", "comment": "" diff --git a/pubs-a.html b/pubs-a.html index 9e3af2c..7f2dcf2 100644 --- a/pubs-a.html +++ b/pubs-a.html @@ -3,7 +3,11 @@

William W. Cohen's Papers: Applications

    -
  1. Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson and William W. Cohen (2024): Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation in progress. +
  2. Cassandra A. Cohen, William W. Cohen (2024): Watch Your Steps: Observable and Modular Chains of Thought in preparation. +
    3. +
  3. Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson and William W. Cohen (2024): Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation in NeurIPS-2024. +
    4. +
  4. Gabriel Sarch, Lawrence Jang, Michael J. Tarr, William W. Cohen, Kenneth Marino, Katerina Fragkiadaki (2024): ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights in NeurIPS-2024.
  5. R. Alex Hofer, Joshua Maynez, Bhuwan Dhingra, Adam Fisch, Amir Globerson and William W. Cohen (2024): Bayesian Prediction-Powered Inference in progress.
    6. diff --git a/pubs-g.html b/pubs-g.html index c970261..3f8da54 100755 --- a/pubs-g.html +++ b/pubs-g.html @@ -1,128 +1,22 @@ -William W. Cohen's Papers: Learning in Graphs +William W. Cohen's Papers: GNAT System -

    William W. Cohen's Papers: Learning in Graphs

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    William W. Cohen's Papers: GNAT System

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    1. Wenhu Chen, William W. Cohen, Michiel De Jong, Nitish Gupta, Alessandro Presta, Pat Verga, John Wieting (2023): QA Is the New KR: Question-Answer Pairs as Knowledge Bases in AAAI-2023.
      • Proposes that symbolic KBs can be replaced with a collection of question-answer pairs automatically generated from a corpus, augmented with entity-linking annotations. Like a symbolic KB, this representation is well-suited to structured queries involving joins and aggregation, and can support 'multi-hop' reasoning. However, it has the advantage that the information in it is closely aligned to likely user information needs, as modeled by the question generation process.
      +
    2. Lidong Bing, William W. Cohen, Bhuwan Dhingra, and Richard C. Wang (2017): Using Graphs of Classifiers to Impose Constraints on Semi-supervised Relation Extraction in IJCAI 2017.
      3. -
    3. William W. Cohen, Fan Yang, and Kathryn Rivard Mazaitis (2020): TensorLog: A Probabilistic Database Implemented Using Deep-Learning Infrastructure in JAIR.
      • Most complete paper on TensorLog, a predecessor of NQL/EmQL that was a Prolog-like logic, not a dataflow query language.
      +
    4. Lidong Bing, Bhuwan Dhingra, Kathryn Mazaitis, Jong Hyuk Park, William W. Cohen (2017): Bootstrapping Distantly Supervised IE using Joint Learning and Small Well-structured Corpora in AAAI 2017.
      5. -
    5. William W. Cohen, Haitian Sun, Alex Hofer, Matthew Siegler (2019): Differentiable Representations For Multihop Inference Rules in arxiv.
      • Earlier version of ICLR paper on NQL.
      +
    6. Lidong Bing, William W. Cohen, Bhuwan Dhingra, and Richard C. Wang (2016): Using Graphs of Classifiers to Impose Constraints on Semi-supervised Relation Extraction in WAKBC-2016.
      7. -
    7. William W. Cohen, Matthew Siegler, Alex Hofer (2019): Neural Query Language: A Knowledge Base Query Language for Tensorflow in arxiv.
      • Earlier version of ICLR paper on NQL focusing on the language constructs used.
      +
    8. William Yang Wang and William W. Cohen (2016): Learning First-Order Logic Embeddings via Matrix Factorization in IJCAI-2016.
      9. -
    9. Haitian Sun, Tania Bedrax-Weiss, William W. Cohen (2019): PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text in EMNLP-2019. -
      10. -
    10. Haitian Sun, William W. Cohen, Lidong Bing (2018): Semi-Supervised Learning with Declaratively Specified Entropy Constraints in NIPS-2018. -
      11. -
    11. Zhilin Yang, Jake (Junbo) Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun (2018): GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations in NIPS-2018. -
      12. -
    12. Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, and William W. Cohen (2018): Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text in EMNLP-2018. -
      13. -
    13. Bhuwan Dhingra, Qiao Jin, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov (2018): Neural Models for Reasoning over Multiple Mentions using Coreference in NAACL-2018. -
      14. -
    14. Fan Yang, Zhilin Yang, William W. Cohen (2017): Differentiable Learning of Logical Rules for Knowledge Base Reasoning in NIPS-2017. -
      15. -
    15. Zihang Dai, Zhilin Yang, William W. Cohen, and Ruslan Salakhutdinov (2017): Good Semi-supervised Learning that Requires a Bad GAN in NIPS-2017. -
      16. -
    16. William W. Cohen and Fan Yang (2017): TensorLog: Deep Learning Meets Probabilistic Databases in arxiv.org 1707.05390. -
      17. -
    17. Bhuwan Dhingra, Zhilin Yang, William W. Cohen, and Ruslan Salakhutdinov (2017): Linguistic Knowledge as Memory for Recurrent Neural Networks in arxiv 1703.02620. -
      18. -
    18. William W. Cohen (2016): TensorLog: A Differentiable Deductive Database in arxiv.org 1605.06523. -
      19. -
    19. Douglas R. Pierce, David P. Redlawsk, and William W. Cohen (2016): Social Influences on Online Political Information Search and Evaluation in Political Behavior DOI 10.1007/s11109-016-9374-4. -
      20. -
    20. Zhilin Yang, Jei Tang, and William W. Cohen (2016): Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs in IJCAI-2016. +
    21. Zhilin Yang, Ruslan Salakhutdinov, William Cohen (2016): Revisiting Semi-Supervised Learning with Graph Embeddings in ICML-2016.
    22. Lidong Bing, Mingyang Ling, Richard C. Wang, William W. Cohen (2016): Distant IE by Bootstrapping Using Lists and Document Structure in AAAI-2016.
      23. -
    23. Bhavana Dalvi and Aditya Mishra and William W. Cohen (2016): Hierarchical Semi-supervised Classification with Incomplete Class Hierarchies in WSDM-2016. -
      24. -
    24. Jay Pujara, Hui Miao, Lise Getoor, and William W. Cohen (2015): Using semantics and statistics to turn data into knowledge in AI Magazine 2015. -
    25. Lidong Bing, Sneha Chaudhari, Richard C. Wang, and William W. Cohen (2015): Improving Distant Supervision for Information Extraction Using Label Propagation Through Lists in EMNLP-2015.
      26. -
    26. Ramnath Balasubramanyan and William W. Cohen (2014): Block-LDA: Jointly Modeling Entity-Annotated Text and Entity-Entity Links in Handbook of Mixed Membership Models and Their Applications. -
      27. -
    27. Partha Pratim Talukdar and William W. Cohen (2014): Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch in AI-Stats 2014. -
      28. -
    28. Frank Lin and William W. Cohen (2012): A General and Scalable Approach to Mixed Membership Clustering in ICDM-2012. -
      29. -
    29. Ramnath Balasubramanyan and William W. Cohen (2012): Entropic Regularization of Mixed-membership Network Models using Pseudo-observations in MLG-2012. -
      30. -
    30. Ramnath Balasubramanyan, Kathryn Rivard, William W. Cohen, Jelena Jakovljevic and John Woolford (2012): Evaluating Joint Modeling of Yeast Biology Literature and Protein-Protein Interaction Networks in BioNLP-2012. -
      31. -
    31. Ni Lao, Tom Mitchell, and William W. Cohen (2011): Random Walk Inference and Learning in A Large Scale Knowledge Base in EMNLP-2011. -
      32. -
    32. Frank Lin and William W. Cohen (2011): Adaptation of Graph-Based Semi-Supervised Methods to Large-Scale Text Data in MLG-2011. -
      33. -
    33. Ramnath Balasubramanyan and William W. Cohen (2011): Block-LDA: Jointly modeling entity-annotated text and entity-entity links in SDM-2011. -
      34. -
    34. Ramnath Balasubramanyan, Frank Lin, and William W. Cohen (2010): Node Clustering in Graphs: An Empirical Study in NIPS-2010 Workshop on Networks Across Disciplines. -
      35. -
    35. Philip Stutz, Abraham Bernstein and William W. Cohen (2010): Signal/Collect: Graph Algorithms for the (Semantic) Web in ISWC-2010. -
      36. -
    36. Einat Minkov and William W. Cohen (2010): Improving Graph-Walk Based Similarity with Reranking: Case Studies for Personal Information Management in TOIS-2010. -
      37. -
    37. Ni Lao and William W. Cohen (2010): Relational Retrieval Using a Combination of Path-Constrained Random Walks in ECML-2010 and MLJ-2010 Special Issue. -
      38. -
    38. Frank Lin and William W. Cohen (2010): Semi-Supervised Classification of Network Data Using Very Few Labels in ASONAM-2010. -
      39. -
    39. Ramnath Balasubramanyan and William W. Cohen (2010): Block-LDA: Jointly modeling entity-annotated text and entity-entity links in ICML-2010 Workshop on Topic Modeling. -
      40. -
    40. Frank Lin and William W. Cohen (2010): Power Iteration Clustering in ICML-2010. -
      41. -
    41. Frank Lin and William W. Cohen (2010): A Very Fast Method for Clustering Big Text Datasets in ECAI-2010. -
      42. -
    42. Ni Lao and William W. Cohen (2010): Fast Query Execution for Retrieval Models based on Path Constrained Random Walks in KDD-2010. -
      43. -
    43. William Cohen (2009): Graph Walks and Graphical Models in SCS Technical Report Collection. -
      44. -
    44. Ramnath Balasubramanyan, Frank Lin, William W. Cohen, Noah A. Smith, and Matthew Hurst (2009): From Episodes to Sagas: Understanding the News by Identifying Temporally Related Story Sequences in ICWSM-2009 (poster). -
      45. -
    45. Andrew Arnold and William W. Cohen (2009): Information Extraction as Link Prediction: Using Curated Citation Networks to Improve Gene Detection in WASA-2009. -
      46. -
    46. Andrew Arnold and William W. Cohen (2009): Information Extraction as Link Prediction: Using Curated Citation Networks to Improve Gene Detection in ICWSM-2009 (poster). -
      47. -
    47. Einat Minkov and William W. Cohen (2008): Learning Graph Walk Based Similarity Measures for Parsed Text in EMNLP-2008. -
      48. -
    48. Einat Minkov, Ramnath Balasubramanyan, and William W. Cohen (2008): Activity-centric Search in Email in AAAI-2008 Workshop on Enhanced Messaging. -
      49. -
    49. Einat Minkov and William W. Cohen (2008): Learning to Walk Structured Text Networks in CMU SCS Technical Report Series (CMU-LTI-08-02). -
      50. -
    50. Ramesh Nallapati, Amr Ahmed, Eric Xing, and William W. Cohen (2008): Joint Latent Topic Models for Text and Citations in KDD-2008. -
      51. -
    51. Ramesh Nallapati and William W. Cohen (2008): Link-PLSA-LDA: A New Unsupervised Model for Topics and Influence of Blogs in ICWSM-2008. -
      52. -
    52. Frank Lin and William W. Cohen (2008): The MultiRank Bootstrap Algorithm: SemiSupervised Political Blog Classification and Ranking Using SemiSupervised Link Classification in ICWSM-2008 (poster). -
      53. -
    53. Frank Lin and William W. Cohen (2008): The MultiRank Bootstrap Algorithm: SemiSupervised Political Blog Classification and Ranking Using SemiSupervised Link Classification in CMU SCS Technical Report Series (CMU-LTI-08-03). -
      54. -
    54. Einat Minkov and William Cohen (2007): Learning to Rank Typed Graph Walks: Local and Global Approaches in WebKDD-2007. -
      55. -
    55. Vitor Carvalho, Wen Wu and William Cohen (2007): Discovering Leadership Roles in Email Workgroups in CEAS-2007. -
      56. -
    56. Zhenzhen Kou, Vitor Carvalho and William Cohen (2007): Online Stacked Graphical Learning in NIPS-07 Workshop on Efficient Machine Learning . -
      57. -
    57. Zhenzhen Kou and William W. Cohen (2007): Stacked Graphical Models for Efficient Inference in Markov Random Fields in SDM-2007. -
      58. -
    58. Zhenzhen Kou, William W. Cohen, and Robert F. Murphy (2007): A Stacked Graphical Model for Associating Information from Text And Images In Figures in PSB-2007. -
      59. -
    59. Einat Minkov and William W. Cohen (2006): An Email and Meeting Assistant using Graph Walks in CEAS-2006. -
      60. -
    60. Einat Minkov, Andrew Ng and William W. Cohen (2006): Contextual Search and Name Disambiguation in Email using Graphs in SIGIR-2006. -
      61. -
    61. William W. Cohen (2006): A Graph-Search Framework for GeneId Ranking (Extended Abstract) in BioNLP'06. -
      62. -
    62. William W. Cohen & Einat Minkov (2006): A Graph-Search Framework for Associating Gene Identifiers with Documents in BMC Bioinformatics. -
      63. -
    63. William W. Cohen (2003): Learning and Discovering Structure in Web Pages in IEEE Data Eng. Bull. 26(3): 3-10 (2003). -
      64. -
    64. William W. Cohen, Andrew McCallum, Dallan Quass (2000): Learning to Understand the Web in IEEE Data Eng. Bull. 23(3): 17-24 (2000). -
      65. -
    65. William W. Cohen (1998): The WHIRL Approach to Information Integration in IEEE Intelligent Systems, Sept/Oct 1998, pp 20--23. -

    [Selected papers| By topic: GNAT System| Retrieval Augmented LMs| Applications| Collaborative Filtering| Intelligent Tutoring| Explanation-Based Learning| Formal Results| Learning in Graphs| Inductive Logic Programming| Neural Knowledge Representation| Topic Modeling| Matching/Data Integration| Deep Learning| Prediction-powered inference| Rule Learning| Text Categorization| Info Extraction/Reading/QA| By year: All papers]

    diff --git a/pubs-r.html b/pubs-r.html index 19d820b..3be351c 100644 --- a/pubs-r.html +++ b/pubs-r.html @@ -1,37 +1,49 @@ -William W. Cohen's Papers: Rule Learning +William W. Cohen's Papers: Retrieval Augmented LMs -

    William W. Cohen's Papers: Rule Learning

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    William W. Cohen's Papers: Retrieval Augmented LMs

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    1. Ni Lao, Einat Minkov, and William W. Cohen (2015): Learning Relational Features with Backward Random Walks in ACL-2015. +
    2. Tal Schuster, Adam D. Lelkes, Haitian Sun, Jai Gupta, Jonathan Berant, William W. Cohen, Donald Metzler (2024): SEMQA: Semi-Extractive Multi-Source Question Answering in NAACL-2024.
      3. -
    3. William Yang Wang, Kathryn Mazaitis, and William W. Cohen (2015): Joint Information Extraction and Reasoning: A Scalable Statistical Relational Learning Approach in ACL-2015. +
    4. Yury Zemlyanskiy, Michiel de Jong, Luke Vilnis, Santiago Ontañón, William W. Cohen, Sumit Sanghai, Joshua Ainslie (2024): MEMORY-VQ: Compression for Tractable Internet-Scale Memory in NAACL-2024.
      5. -
    5. William Yang Wang, Kathryn Mazaitis, and William W. Cohen (2014): Structure Learning via Parameter Learning in CIKM-2014. +
    6. Haitian Sun, William W. Cohen, Ruslan Salakhutdinov (2023): Answering Ambiguous Questions with a Database of Questions, Answers, and Revisions in progress.
      • Following up the 'QA is the new KR' paper, we present a new collection of question-answer pairs automatically generated from Wikipedia which are more specific and ambiiguous than generated questions used in prior work, and show that this can be used to answer ambiguous questions. On the challenging ASQA benchmark, which requires generating long-form answers that summarize the multiple answers to an ambiguous question, our method improves performance by 10-15%. The new queston DB can also be used to improve diverse passage retrieval.
      7. -
    7. William W. Cohen, Matthew Hurst & Lee S. Jensen (2003): A Flexible Learning System for Wrapping Tables and Lists in HTML Documents in Web Document Analysis: Challenges and Opportunities, ed. Antonacopoulos & Hu, Word Scientific Publishing. +
    8. Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Sumit Sanghai, William W. Cohen, Joshua Ainslie (2023): GLIMMER: generalized late-interaction memory reranker in progress.
      9. -
    9. William W. Cohen, Matthew Hurst & Lee S. Jensen (2002): A Flexible Learning System for Wrapping Tables and Lists in HTML Documents in WWW 2002: 232-241. +
    10. Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen (2023): Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute in ICML-2023.
      11. -
    11. William W. Cohen and Yoram Singer (1999): Simple, Fast, and Effective Rule Learner in AAAI/IAAI 1999: 335-342. +
    12. Wenhu Chen, Hexiang Hu, Xi Chen, Pat Verga, William W. Cohen (2023): MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text in EACL-2023.
      13. -
    13. William W. Cohen & Yoram Singer (1999): Context-sensitive learning methods for text categorization in ACM Trans. Inf. Syst. 17(2): 141-173 (1999). +
    14. Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William Cohen (2023): FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference in ACL-2023 (Findings).
      15. -
    15. Chumki Basu, Haym Hirsh, William W. Cohen (1998): Recommendation as Classification: Using Social and Content-Based Information in Recommendation. in AAAI/IAAI 1998: 714-720. +
    16. Wenhu Chen, Hexiang Hu, Chitwan Saharia, William W. Cohen (2023): Re-Imagen: Retrieval-Augmented Text-to-Image Generator in ICLR-2023.
      17. -
    17. William W. Cohen and Daniel Kudenko (1997): Transferring and Retraining Learned Information Filters in AAAI/IAAI 1997: 583-590. +
    18. Wenhu Chen, William W. Cohen, Michiel De Jong, Nitish Gupta, Alessandro Presta, Pat Verga, John Wieting (2023): QA Is the New KR: Question-Answer Pairs as Knowledge Bases in AAAI-2023.
      • Proposes that symbolic KBs can be replaced with a collection of question-answer pairs automatically generated from a corpus, augmented with entity-linking annotations. Like a symbolic KB, this representation is well-suited to structured queries involving joins and aggregation, and can support 'multi-hop' reasoning. However, it has the advantage that the information in it is closely aligned to likely user information needs, as modeled by the question generation process.
      19. -
    19. William W. Cohen (1996): Learning Trees and Rules with Set-valued Features in AAAI/IAAI, Vol. 1 1996: 709-716. +
    20. Haitian Sun, William W. Cohen, Ruslan Salakhutdinov (2023): Scenario-based Question Answering with Interacting Contextual Properties in ICLR-2023.
      21. -
    21. William W. Cohen (1996): Learning Rules that Classify E-Mail in AAAI Spring Symposium on ML and IR 1996. +
    22. Bernd Bohnet, Vinh Q. Tran, Pat Verga, Roee Aharoni, Daniel Andor, Livio Baldini Soares, Jacob Eisenstein, Kuzman Ganchev, Jonathan Herzig, Kai Hui, Tom Kwiatkowski, Ji Ma, Jianmo Ni, Tal Schuster, William W. Cohen, Michael Collins, Dipanjan Das, Donald Metzler, Slav Petrov, and Kellie Webster (2022): Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models in progress.
      23. -
    23. William W. Cohen and Yoram Singer (1996): Learning to Query the Web in AAAI Workshop on Internet-Based Information Access Systems 1996. +
    24. Wenhu Chen, Pat Verga, Michiel de Jong, John Wieting, William W. Cohen (2022): Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering in EACL-2022.
      • Extends the techniques of Mention Memory in several important ways. (1) The memory is a memory of generated question-answer pairs, which is more interpretable than neural entity-mention encodings; (2) it is based on pre-trained T5, not a custom Transformer; and (3) it allows use of the token-level encoding of retrieved QA pairs as well as neural encodings of them for reasoning. Using QA pairs instead of passages allows a clever pre-training trick for learning to retrieve, and the model greatly outperfoms a prior similar model (i.e., RePAQ) on smaller QA benchmarks.
      25. -
    25. William W. Cohen and Yoram Singer (1996): Context-sensitive learning methods for text categorization in SIGIR 1996: 307-315. +
    26. Vidhisha Balachandran and Bhuwan Dhingra and Haitian Sun and Michael Collins and William W. Cohen (2021): Investigating the Effect of Background Knowledge on Natural Questions in DeeLIO-2021.
      • Proceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures
      27. -
    27. William W. Cohen (1995): Fast effective rule induction in ICML 1995: 115-123. +
    28. Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William Cohen (2021): Mention Memory: incorporating textual knowledge into Transformers through entity mention attention in ICLR 2021.
      • Similar to the Entities-as-Experts model, but uses a much larger memory of entity mentions, which allows the model to potentially provide meaningful provenance for information. The model, called TOME, outperforms Entities-as-Experts on several tasks, and required some non-trivial technical innovations relating to memory pre-training and efficient retrieval.
      29. -
    29. William W. Cohen (1993): Efficient pruning methods for separate-and-conquer rule learning systems in IJCAI 1993: 988-994. +
    30. Haitian Sun, William W. Cohen, Ruslan Salakhutdinov (2021): End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents in preparation.
      • Adapts many of the ideas used for multihop KBQA to a new task - answering multihop questions over a large document. Retrieval steps in this "DocHopper" system retrieve passages of a document, and the retrieved items are combined with a question neurally: i.e., rather than appending text to a question and re-encoding that discrete object, what is retrieved is a vector summary of the document, which is mixed with the previous question encoding. This is fast, fully differentiable, allows retrieval of large document subsections, and gets a new SOTA on three datasets.
      +
      31. +
    31. Haitian Sun, Pat Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W. Cohen (2021): Reasoning Over Virtual Knowledge Bases With Open Predicate Relations in ICML2021.
      • Modifies the FILM model by using a virtual KB of small text passages containing pairs of entities. This required adding a Matching-the-Blanks pretraining phase, but got strong results on a number of QA-from-corpora tasks.
      +
      32. +
    32. Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Wang, William W. Cohen (2021): Open Question Answering Over Tables and Text in ICLR-2021.
      • Answering open QA multi-hop questions over tables and text with a clever ``early fusion'' idea, which proposes and indexes likely reasoning chains, and uses large-document Transformers to merge these noisy evidence chains.
      +
      33. +
    33. Pat Verga, Haitian Sun, Livio Baldini Soares, and William W. Cohen (2021): Adaptable and Interpretable Neural Memory Over Symbolic Knowledge in NAACL-2021.
      • Most recent paper on Fact-Injected Language Model (FILM), which includes an Entities-as-Experts style memory of neural entity encodings, plus a second "fact memory" of KG triples. FILM has good results on KBQA tasks, and allows one to use an edited KB with retraining.
      +
      34. +
    34. Bill Yuchen Lin, Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Xiang Ren, William W. Cohen (2020): Differentiable Open-Ended Commonsense Reasoning in NAACL-2021.
      • Extends DrKIT's virtual KB to a corpus of documents of common-sense statements ("facts"). In DrFact, entities are replaced by noisy and ambiguous concepts, and navigation is between documents with overlapping sets of mentions. Also introduces new "open" tasks for common-sense QA.
      +
      35. +
    35. Pat Verga, Haitian Sun, Livio Baldini Soares, and William W. Cohen (2020): Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge in arxiv.
      • Earlier draft of the NAACL paper on FILM (Fact-Injected LM).
      +
      36. +
    36. Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen (2020): Differentiable Reasoning over a Virtual Knowledge Base in ICLR-2020.
      • Describes DrKIT, which allows one to answer multihop chain queries on a "virtual KB"---a corpus of entity-linked documents. In DrKIT, entity mentions are indexed for neural retrieval with a rich representation of their context, and reasoning consists of navigating between co-occurring mentions.

    [Selected papers| By topic: GNAT System| Retrieval Augmented LMs| Applications| Collaborative Filtering| Intelligent Tutoring| Explanation-Based Learning| Formal Results| Learning in Graphs| Inductive Logic Programming| Neural Knowledge Representation| Topic Modeling| Matching/Data Integration| Deep Learning| Prediction-powered inference| Rule Learning| Text Categorization| Info Extraction/Reading/QA| By year: All papers]

    diff --git a/pubs-s.html b/pubs-s.html index f412655..8768ede 100644 --- a/pubs-s.html +++ b/pubs-s.html @@ -4,7 +4,11 @@

    Selected and/or recent papers by William W. Cohen

    Recent papers: 2024

      -
    1. Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson and William W. Cohen (2024): Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation in progress. +
    2. Cassandra A. Cohen, William W. Cohen (2024): Watch Your Steps: Observable and Modular Chains of Thought in preparation. +
      3. +
    3. Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson and William W. Cohen (2024): Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation in NeurIPS-2024. +
      4. +
    4. Gabriel Sarch, Lawrence Jang, Michael J. Tarr, William W. Cohen, Kenneth Marino, Katerina Fragkiadaki (2024): ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights in NeurIPS-2024.
    5. R. Alex Hofer, Joshua Maynez, Bhuwan Dhingra, Adam Fisch, Amir Globerson and William W. Cohen (2024): Bayesian Prediction-Powered Inference in progress.
      6. diff --git a/pubs.html b/pubs.html index b03c645..f90a805 100644 --- a/pubs.html +++ b/pubs.html @@ -4,7 +4,11 @@

      Papers by William W. Cohen

      Papers published in 2024

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      1. Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson and William W. Cohen (2024): Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation in progress. +
      2. Cassandra A. Cohen, William W. Cohen (2024): Watch Your Steps: Observable and Modular Chains of Thought in preparation. +
        3. +
      3. Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson and William W. Cohen (2024): Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation in NeurIPS-2024. +
        4. +
      4. Gabriel Sarch, Lawrence Jang, Michael J. Tarr, William W. Cohen, Kenneth Marino, Katerina Fragkiadaki (2024): ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights in NeurIPS-2024.
      5. R. Alex Hofer, Joshua Maynez, Bhuwan Dhingra, Adam Fisch, Amir Globerson and William W. Cohen (2024): Bayesian Prediction-Powered Inference in progress.