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2020 – today
- 2024
[c36]Michael Xieyang Liu
, Frederick Liu, Alexander J. Fiannaca, Terry Koo, Lucas Dixon, Michael Terry, Carrie J. Cai:
"We Need Structured Output": Towards User-centered Constraints on Large Language Model Output. CHI Extended Abstracts 2024: 10:1-10:9- [c35]Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon:
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. CHI Extended Abstracts 2024: 216:1-216:7 - [c34]Tyler A. Chang, Katrin Tomanek, Jessica Hoffmann, Nithum Thain, Erin MacMurray van Liemt, Kathleen S. Meier-Hellstern, Lucas Dixon:
Detecting Hallucination and Coverage Errors in Retrieval Augmented Generation for Controversial Topics. LREC/COLING 2024: 4729-4743 - [c33]Dan Friedman, Andrew Kyle Lampinen, Lucas Dixon, Danqi Chen, Asma Ghandeharioun:
Interpretability Illusions in the Generalization of Simplified Models. ICML 2024 - [c32]Asma Ghandeharioun, Avi Caciularu, Adam Pearce, Lucas Dixon, Mor Geva:
Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models. ICML 2024 - [c31]Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet, Felipe Llinares-López, Jessica Hoffmann, Lucas Dixon, Michal Valko, Mathieu Blondel:
Decoding-time Realignment of Language Models. ICML 2024 - [i34]Asma Ghandeharioun, Avi Caciularu, Adam Pearce, Lucas Dixon, Mor Geva:
Patchscopes: A Unifying Framework for Inspecting Hidden Representations of Language Models. CoRR abs/2401.06102 (2024) - [i33]Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet, Felipe Llinares, Jessica Hoffmann, Lucas Dixon, Michal Valko, Mathieu Blondel:
Decoding-time Realignment of Language Models. CoRR abs/2402.02992 (2024) - [i32]Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, Lucas Dixon:
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. CoRR abs/2402.10524 (2024) - [i31]Tyler A. Chang, Katrin Tomanek, Jessica Hoffmann, Nithum Thain, Erin van Liemt, Kathleen S. Meier-Hellstern, Lucas Dixon:
Detecting Hallucination and Coverage Errors in Retrieval Augmented Generation for Controversial Topics. CoRR abs/2403.08904 (2024) - [i30]Hakim Sidahmed, Samrat Phatale, Alex Hutcheson, Zhuonan Lin, Zhang Chen, Zac Yu, Jarvis Jin, Roman Komarytsia, Christiane Ahlheim, Yonghao Zhu, Simral Chaudhary, Bowen Li, Saravanan Ganesh, Bill Byrne, Jessica Hoffmann, Hassan Mansoor, Wei Li, Abhinav Rastogi, Lucas Dixon:
PERL: Parameter Efficient Reinforcement Learning from Human Feedback. CoRR abs/2403.10704 (2024) - [i29]Michael Xieyang Liu, Frederick Liu, Alexander J. Fiannaca, Terry Koo, Lucas Dixon, Michael Terry, Carrie J. Cai:
"We Need Structured Output": Towards User-centered Constraints on Large Language Model Output. CoRR abs/2404.07362 (2024) - [i28]Ian Tenney, Ryan Mullins, Bin Du, Shree Pandya, Minsuk Kahng, Lucas Dixon:
Interactive Prompt Debugging with Sequence Salience. CoRR abs/2404.07498 (2024) - [i27]Asma Ghandeharioun, Ann Yuan, Marius Guerard, Emily Reif, Michael A. Lepori, Lucas Dixon:
Who's asking? User personas and the mechanics of latent misalignment. CoRR abs/2406.12094 (2024) - 2023
- [j10]Varada Kolhatkar, Nithum Thain, Jeffrey Sorensen, Lucas Dixon, Maite Taboada:
Classifying constructive comments. First Monday 28(4) (2023) - [c30]Léo Laugier, Raghuram Vadapalli, Thomas Bonald, Lucas Dixon:
KNNs of Semantic Encodings for Rating Prediction. CIC 2023: 82-91 - [c29]Maximilian Mozes, Jessica Hoffmann, Katrin Tomanek, Muhamed Kouate, Nithum Thain, Ann Yuan, Tolga Bolukbasi, Lucas Dixon:
Towards Agile Text Classifiers for Everyone. EMNLP (Findings) 2023: 400-414 - [c28]Scott Sanner, Krisztian Balog, Filip Radlinski, Ben Wedin, Lucas Dixon:
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. RecSys 2023: 890-896 - [c27]Jeffrey Sorensen, Katerina Korre, John Pavlopoulos, Katrin Tomanek, Nithum Thain, Lucas Dixon, Léo Laugier:
JUAGE at SemEval-2023 Task 10: Parameter Efficient Classification. SemEval@ACL 2023: 1195-1203 - [i26]Léo Laugier, Thomas Bonald, Lucas Dixon, Raghuram Vadapalli:
KNNs of Semantic Encodings for Rating Prediction. CoRR abs/2302.00412 (2023) - [i25]Maximilian Mozes, Jessica Hoffmann, Katrin Tomanek, Muhamed Kouate, Nithum Thain, Ann Yuan, Tolga Bolukbasi, Lucas Dixon:
Towards Agile Text Classifiers for Everyone. CoRR abs/2302.06541 (2023) - [i24]Maximilian Mozes, Tolga Bolukbasi, Ann Yuan, Frederick Liu, Nithum Thain, Lucas Dixon:
Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning. CoRR abs/2302.06598 (2023) - [i23]Kelvin Guu, Albert Webson, Ellie Pavlick, Lucas Dixon, Ian Tenney, Tolga Bolukbasi:
Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs. CoRR abs/2303.08114 (2023) - [i22]Konstantina Christakopoulou, Alberto Lalama, Cj Adams, Iris Qu, Yifat Amir, Samer Chucri, Pierce Vollucci, Fabio Soldo, Dina Bseiso, Sarah Scodel, Lucas Dixon, Ed H. Chi, Minmin Chen:
Large Language Models for User Interest Journeys. CoRR abs/2305.15498 (2023) - [i21]Scott Sanner, Krisztian Balog, Filip Radlinski, Ben Wedin, Lucas Dixon:
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. CoRR abs/2307.14225 (2023) - [i20]Michael Terry, Chinmay Kulkarni, Martin Wattenberg, Lucas Dixon, Meredith Ringel Morris:
AI Alignment in the Design of Interactive AI: Specification Alignment, Process Alignment, and Evaluation Support. CoRR abs/2311.00710 (2023) - [i19]Dan Friedman, Andrew K. Lampinen, Lucas Dixon, Danqi Chen, Asma Ghandeharioun:
Interpretability Illusions in the Generalization of Simplified Models. CoRR abs/2312.03656 (2023) - 2022
- [j9]Alexandros Xenos, John Pavlopoulos, Ion Androutsopoulos, Lucas Dixon, Jeffrey Sorensen, Léo Laugier:
Toxicity detection sensitive to conversational context. First Monday 27(9) (2022) - [c26]Nan Du, Yanping Huang, Andrew M. Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten P. Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathleen S. Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui:
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. ICML 2022: 5547-5569 - [c25]Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim:
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis. NeurIPS 2022 - [c24]Filip Radlinski, Krisztian Balog, Fernando Diaz, Lucas Dixon, Ben Wedin:
On Natural Language User Profiles for Transparent and Scrutable Recommendation. SIGIR 2022: 2863-2874 - [i18]Filip Radlinski, Krisztian Balog, Fernando Diaz, Lucas Dixon, Ben Wedin:
On Natural Language User Profiles for Transparent and Scrutable Recommendation. CoRR abs/2205.09403 (2022) - [i17]Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim:
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis. CoRR abs/2206.09046 (2022) - [i16]Lucas Dixon:
Basic Elements of Logical Graphs. CoRR abs/2208.03194 (2022) - 2021
- [c23]Léo Laugier, John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon:
Civil Rephrases Of Toxic Texts With Self-Supervised Transformers. EACL 2021: 1442-1461 - [i15]Léo Laugier, John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon:
Civil Rephrases Of Toxic Texts With Self-Supervised Transformers. CoRR abs/2102.05456 (2021) - [i14]Federico López, Martin Scholz, Jessica Yung, Marie Pellat, Michael Strube, Lucas Dixon:
Augmenting the User-Item Graph with Textual Similarity Models. CoRR abs/2109.09358 (2021) - [i13]Alexandros Xenos, John Pavlopoulos, Ion Androutsopoulos, Lucas Dixon, Jeffrey Sorensen, Léo Laugier:
Toxicity Detection can be Sensitive to the Conversational Context. CoRR abs/2111.10223 (2021) - [i12]Nan Du, Yanping Huang, Andrew M. Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathy Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui:
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. CoRR abs/2112.06905 (2021) - 2020
- [c22]John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon, Nithum Thain, Ion Androutsopoulos:
Toxicity Detection: Does Context Really Matter? ACL 2020: 4296-4305 - [c21]Ilan Price, Jordan Gifford-Moore, Jory Flemming, Saul Musker, Maayan Roichman, Guillaume Sylvain, Nithum Thain, Lucas Dixon, Jeffrey Sorensen:
Six Attributes of Unhealthy Conversations. WOAH 2020: 114-124 - [i11]Varada Kolhatkar, Nithum Thain, Jeffrey Sorensen, Lucas Dixon, Maite Taboada:
Classifying Constructive Comments. CoRR abs/2004.05476 (2020) - [i10]John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon, Nithum Thain, Ion Androutsopoulos:
Toxicity Detection: Does Context Really Matter? CoRR abs/2006.00998 (2020) - [i9]Ilan Price, Jordan Gifford-Moore, Jory Flemming, Saul Musker, Maayan Roichman, Guillaume Sylvain, Nithum Thain, Lucas Dixon, Jeffrey Sorensen:
Six Attributes of Unhealthy Conversation. CoRR abs/2010.07410 (2020)
2010 – 2019
- 2019
- [c20]John Pavlopoulos, Nithum Thain, Lucas Dixon, Ion Androutsopoulos:
ConvAI at SemEval-2019 Task 6: Offensive Language Identification and Categorization with Perspective and BERT. SemEval@NAACL-HLT 2019: 571-576 - [c19]Daniel Borkan, Lucas Dixon, Jeffrey Sorensen, Nithum Thain, Lucy Vasserman:
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification. WWW (Companion Volume) 2019: 491-500 - [c18]Lora Aroyo, Lucas Dixon, Nithum Thain, Olivia Redfield, Rachel Rosen:
Crowdsourcing Subjective Tasks: The Case Study of Understanding Toxicity in Online Discussions. WWW (Companion Volume) 2019: 1100-1105 - [i8]Daniel Borkan, Lucas Dixon, John Li, Jeffrey Sorensen, Nithum Thain, Lucy Vasserman:
Limitations of Pinned AUC for Measuring Unintended Bias. CoRR abs/1903.02088 (2019) - [i7]Daniel Borkan, Lucas Dixon, Jeffrey Sorensen, Nithum Thain, Lucy Vasserman:
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification. CoRR abs/1903.04561 (2019) - 2018
- [c17]Justine Zhang, Jonathan P. Chang, Cristian Danescu-Niculescu-Mizil, Lucas Dixon, Yiqing Hua, Dario Taraborelli, Nithum Thain:
Conversations Gone Awry: Detecting Early Signs of Conversational Failure. ACL (1) 2018: 1350-1361 - [c16]Lucas Dixon, John Li, Jeffrey Sorensen, Nithum Thain, Lucy Vasserman:
Measuring and Mitigating Unintended Bias in Text Classification. AIES 2018: 67-73 - [c15]Amy S. Bruckman, Jennifer E. Below, Lucas Dixon, Casey Fiesler, Eric E. Gilbert, Sarah A. Gilbert, J. Nathan Matias:
Managing Deviant Behavior in Online Communities III. CHI Extended Abstracts 2018 - [c14]Yiqing Hua, Cristian Danescu-Niculescu-Mizil, Dario Taraborelli, Nithum Thain, Jeffery Sorensen, Lucas Dixon:
WikiConv: A Corpus of the Complete Conversational History of a Large Online Collaborative Community. EMNLP 2018: 2818-2823 - [i6]Justine Zhang, Jonathan P. Chang, Cristian Danescu-Niculescu-Mizil, Lucas Dixon, Yiqing Hua, Nithum Thain, Dario Taraborelli:
Conversations Gone Awry: Detecting Early Signs of Conversational Failure. CoRR abs/1805.05345 (2018) - [i5]Yiqing Hua, Cristian Danescu-Niculescu-Mizil, Dario Taraborelli, Nithum Thain, Jeffery Sorensen, Lucas Dixon:
WikiConv: A Corpus of the Complete Conversational History of a Large Online Collaborative Community. CoRR abs/1810.13181 (2018) - 2017
- [c13]Ellery Wulczyn, Nithum Thain, Lucas Dixon:
Ex Machina: Personal Attacks Seen at Scale. WWW 2017: 1391-1399 - 2016
- [j8]Lucas Dixon, Thomas Ristenpart, Thomas Shrimpton:
Network Traffic Obfuscation and Automated Internet Censorship. IEEE Secur. Priv. 14(6): 43-53 (2016) - [i4]Lucas Dixon, Thomas Ristenpart, Thomas Shrimpton:
Network Traffic Obfuscation and Automated Internet Censorship. CoRR abs/1605.04044 (2016) - [i3]Ellery Wulczyn, Nithum Thain, Lucas Dixon:
Ex Machina: Personal Attacks Seen at Scale. CoRR abs/1610.08914 (2016) - 2015
- [j7]Alan Bundy, Flaminia Cavallo, Lucas Dixon, Moa Johansson, Roy L. McCasland:
The Theory behind Theory Mine. IEEE Intell. Syst. 30(4): 64-69 (2015) - 2013
- [j6]Lucas Dixon, Aleks Kissinger:
Open-graphs and monoidal theories. Math. Struct. Comput. Sci. 23(2): 308-359 (2013) - 2012
- [j5]Omar Montaño-Rivas, Roy L. McCasland, Lucas Dixon, Alan Bundy:
Scheme-based theorem discovery and concept invention. Expert Syst. Appl. 39(2): 1637-1646 (2012) - 2011
- [j4]Moa Johansson, Lucas Dixon, Alan Bundy:
Conjecture Synthesis for Inductive Theories. J. Autom. Reason. 47(3): 251-289 (2011) - [c12]Iain Whiteside, David Aspinall, Lucas Dixon, Gudmund Grov:
Towards Formal Proof Script Refactoring. Calculemus/MKM 2011: 260-275 - 2010
- [c11]Moa Johansson, Lucas Dixon, Alan Bundy:
Dynamic Rippling, Middle-Out Reasoning and Lemma Discovery. Verification, Induction, Termination Analysis 2010: 102-116 - [c10]Ewen Maclean, Andrew Ireland, Lucas Dixon, Robert Atkey:
Refinement and Term Synthesis in Loop Invariant Generation. WING@ETAPS/IJCAR 2010: 167-182 - [c9]Moa Johansson, Lucas Dixon, Alan Bundy:
Case-Analysis for Rippling and Inductive Proof. ITP 2010: 291-306 - [c8]Omar Montaño-Rivas, Roy L. McCasland, Lucas Dixon, Alan Bundy:
Scheme-Based Synthesis of Inductive Theories. MICAI (1) 2010: 348-361 - [c7]Lucas Dixon, Ross Duncan, Aleks Kissinger:
Open Graphs and Computational Reasoning. DCM 2010: 169-180 - [i2]Lucas Dixon, Aleks Kissinger:
Open Graphs and Monoidal Theories. CoRR abs/1011.4114 (2010)
2000 – 2009
- 2009
- [j3]Lucas Dixon, Ross Duncan:
Graphical reasoning in compact closed categories for quantum computation. Ann. Math. Artif. Intell. 56(1): 23-42 (2009) - [j2]Lucas Dixon, Alan Smaill, Tracy Tsang:
Plans, Actions and Dialogues Using Linear Logic. J. Log. Lang. Inf. 18(2): 251-289 (2009) - [e1]Jacques Carette, Lucas Dixon, Claudio Sacerdoti Coen, Stephen M. Watt:
Intelligent Computer Mathematics, 16th Symposium, Calculemus 2009, 8th International Conference, MKM 2009, Held as Part of CICM 2009, Grand Bend, Canada, July 6-12, 2009. Proceedings. Lecture Notes in Computer Science 5625, Springer 2009, ISBN 978-3-642-02613-3 [contents] - [i1]Lucas Dixon, Ross Duncan:
Graphical Reasoning in Compact Closed Categories for Quantum Computation. CoRR abs/0902.0514 (2009) - 2008
- [c6]Lucas Dixon, Ross Duncan:
Extending Graphical Representations for Compact Closed Categories with Applications to Symbolic Quantum Computation. AISC/MKM/Calculemus 2008: 77-92 - 2006
- [b1]Lucas Dixon:
A proof planning framework for Isabelle. University of Edinburgh, UK, 2006 - [j1]Lucas Dixon, Jacques D. Fleuriot:
A proof-centric approach to mathematical assistants. J. Appl. Log. 4(4): 505-532 (2006) - [c5]Moa Johansson, Alan Bundy, Lucas Dixon:
Best-First Rippling. Reasoning, Action and Interaction in AI Theories and Systems 2006: 83-100 - 2005
- [c4]Bin Yang, Alan Bundy, Alan Smaill, Lucas Dixon:
Deductive synthesis of workflows for e-Science. CCGRID 2005: 168-175 - [c3]Alan Bundy, Lucas Dixon, Jeremy Gow, Jacques D. Fleuriot:
Constructing Induction Rules for Deductive Synthesis Proofs. CLASE 2005: 3-21 - 2004
- [c2]Lucas Dixon, Jacques D. Fleuriot:
Higher Order Rippling in IsaPlanner. TPHOLs 2004: 83-98 - 2003
- [c1]Lucas Dixon, Jacques D. Fleuriot:
IsaPlanner: A Prototype Proof Planner in Isabelle. CADE 2003: 279-283
Coauthor Index
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