Probabilities of extinction, weak extinction, permanence, and mutual exclusion in discrete, competitive, Lotka-Volterra systems that involve invading species. - David M. Chan; John E. Franke (Math. Comput. Model., 2004)

Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding. - Thayne T. Walker; David M. Chan; Nathan R. Sturtevant (ICAPS, 2017)

Rapid Randomized Restarts for Multi-Agent Path Finding: Preliminary Results. - Liron Cohen 002; Sven Koenig; T. K. Satish Kumar; Glenn Wagner; Howie Choset; David M. Chan; Nathan R. Sturtevant (AAMAS, 2018)

T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data. - David M. Chan; Roshan Rao; Forrest Huang; John F. Canny (SBAC-PAD, 2018)

Rapid Randomized Restarts for Multi-Agent Path Finding Solvers. - Liron Cohen 002; Glenn Wagner; David M. Chan; Howie Choset; Nathan R. Sturtevant; Sven Koenig; T. K. Satish Kumar (SOCS, 2018)

Diagnostic Visualization for Deep Neural Networks Using Stochastic Gradient Langevin Dynamics. - Biye Jiang; David M. Chan; Tianhao Zhang; John F. Canny (CoRR, 2018)

ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations. - Daniel Seita; David M. Chan; Roshan Rao; Chen Tang; Mandi Zhao; John F. Canny (CoRR, 2019)

GPU accelerated t-distributed stochastic neighbor embedding. - David M. Chan; Roshan Rao; Forrest Huang; John F. Canny (J. Parallel Distributed Comput., 2019)

Active Learning for Video Description with Cluster-Regularized Ensemble Ranking. - David M. Chan; Sudheendra Vijayanarasimhan; David A. Ross; John F. Canny (ACCV (5), 2020)

Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. - Eliza Kosoy; Jasmine Collins; David M. Chan; Deepak Pathak; Pulkit Agrawal 001; Alison Gopnik (CogSci, 2020)

Exploring Exploration: Comparing Children with RL Agents in Unified Environments. - Eliza Kosoy; Jasmine Collins; David M. Chan; Jessica B. Hamrick; Sandy H. Huang; Alison Gopnik; John F. Canny (CoRR, 2020)

A Dataset and Benchmarks for Multimedia Social Analysis. - Bofan Xue; David M. Chan; John F. Canny (CoRR, 2020)

A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery. - Aatif Jiwani; Shubhrakanti Ganguly; Chao Ding; Nan Zhou; David M. Chan (CoRR, 2021)

Learning Causal Overhypotheses through Exploration in Children and Computational Models. - Eliza Kosoy; Adrian Liu; Jasmine Collins; David M. Chan; Jessica B. Hamrick; Nan Rosemary Ke; Sandy H. Huang; Bryanna Kaufmann; John F. Canny; Alison Gopnik (CLeaR, 2022)

Learning Causal Overhypotheses through Exploration in Children and Computational Models. - Eliza Kosoy; Adrian Liu; Jasmine Collins; David M. Chan; Jessica B. Hamrick; Sandy Han Huang; Nan Rosemary Ke; Bryanna Kaufmann; Alison Gopnik (CogSci, 2022)

What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics. - David M. Chan; Austin Myers; Sudheendra Vijayanarasimhan; David A. Ross; Bryan Seybold; John F. Canny (CVPR Workshops, 2022)

Multi-Modal Pre-Training for Automated Speech Recognition. - David M. Chan; Shalini Ghosh; Debmalya Chakrabarty; Björn Hoffmeister (ICASSP, 2022)

Content-Context Factorized Representations for Automated Speech Recognition. - David M. Chan; Shalini Ghosh (INTERSPEECH, 2022)

Towards Understanding How Machines Can Learn Causal Overhypotheses. - Eliza Kosoy; David M. Chan; Adrian Liu; Jasmine Collins; Bryanna Kaufmann; Sandy Han Huang; Jessica B. Hamrick; John F. Canny; Nan Rosemary Ke; Alison Gopnik (CoRR, 2022)

Towards Understanding How Machines Can Learn Causal Overhypotheses. - Eliza Kosoy; David M. Chan; Adrian Liu; Jasmine Collins; Jessica B. Hamrick; Sandy Han Huang; Nan Rosemary Ke; Emily Rose Reagan; John F. Canny; Alison Gopnik (CogSci, 2023)

CLAIR: Evaluating Image Captions with Large Language Models. - David M. Chan; Suzanne Petryk; Joseph Gonzalez 001; Trevor Darrell; John F. Canny (EMNLP, 2023)

Domain Adaptation with External Off-Policy Acoustic Catalogs for Scalable Contextual End-to-End Automated Speech Recognition. - David M. Chan; Shalini Ghosh; Ariya Rastrow; Björn Hoffmeister (ICASSP, 2023)

Using External Off-Policy Speech-To-Text Mappings in Contextual End-To-End Automated Speech Recognition. - David M. Chan; Shalini Ghosh; Ariya Rastrow; Björn Hoffmeister (CoRR, 2023)

IC3: Image Captioning by Committee Consensus. - David M. Chan; Austin Myers; Sudheendra Vijayanarasimhan; David A. Ross; John F. Canny (CoRR, 2023)

Distribution Aware Metrics for Conditional Natural Language Generation. - David M. Chan; Yiming Ni; David A. Ross; Sudheendra Vijayanarasimhan; Austin Myers; John F. Canny (LREC/COLING, 2024)

Multi-Stage Multi-Modal Pre-Training for Automatic Speech Recognition. - Yash Jain; David M. Chan; Pranav Dheram; Aparna Khare; Olabanji Shonibare; Venkatesh Ravichandran; Shalini Ghosh (LREC/COLING, 2024)

See, Say, and Segment: Teaching LMMs to Overcome False Premises. - Tsung-Han Wu; Giscard Biamby; David M. Chan; Lisa Dunlap; Ritwik Gupta; Xudong Wang 007; Joseph E. Gonzalez; Trevor Darrell (CVPR, 2024)

Virtual Personas for Language Models via an Anthology of Backstories. - Suhong Moon; Marwa Abdulhai; Minwoo Kang; Joseph Suh; Widyadewi Soedarmadji; Eran Kohen Behar; David M. Chan (EMNLP, 2024)

Anim-400K: A Large-Scale Dataset for Automated End to End Dubbing of Video. - Kevin Cai; Chonghua Liu; David M. Chan (ICASSP, 2024)

Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition. - David M. Chan; Shalini Ghosh; Hitesh Tulsiani; Ariya Rastrow; Björn Hoffmeister (ICASSP, 2024)

Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification. - Anirudh S. Sundar; Chao-Han Huck Yang; David M. Chan; Shalini Ghosh; Venkatesh Ravichandran; Phani Sankar Nidadavolu (ICASSP Workshops, 2024)

An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems. - Hitesh Tulsiani; David M. Chan; Shalini Ghosh; Garima Lalwani; Prabhat Pandey; Ankish Bansal; Sri Garimella; Ariya Rastrow; Björn Hoffmeister (ICML, 2024)

ALOHa: A New Measure for Hallucination in Captioning Models. - Suzanne Petryk; David M. Chan; Anish Kachinthaya; Haodi Zou; John F. Canny; Joseph Gonzalez 001; Trevor Darrell (NAACL (Short Papers), 2024)

Visual Haystacks: Answering Harder Questions About Sets of Images. - Tsung-Han Wu; Giscard Biamby; Jerome Quenum; Ritwik Gupta; Joseph E. Gonzalez; Trevor Darrell; David M. Chan (CoRR, 2024)

Rediscovering the Latent Dimensions of Personality with Large Language Models as Trait Descriptors. - Joseph Suh; Suhong Moon; Minwoo Kang; David M. Chan (CoRR, 2024)

CLAIR-A: Leveraging Large Language Models to Judge Audio Captions. - Tsung-Han Wu; Joseph E. Gonzalez; Trevor Darrell; David M. Chan (CoRR, 2024)

Analyzing The Language of Visual Tokens. - David M. Chan; Rodolfo Corona; Joonyong Park; Cheol Jun Cho; Yutong Bai; Trevor Darrell (CoRR, 2024)

Enough Coin Flips Can Make LLMs Act Bayesian. - Ritwik Gupta; Rodolfo Corona; Jiaxin Ge; Eric Wang; Dan Klein 001; Trevor Darrell; David M. Chan (ACL (1), 2025)

Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark. - Tsung-Han Wu; Giscard Biamby; Jerome Quenum; Ritwik Gupta; Joseph E. Gonzalez; Trevor Darrell; David M. Chan (ICLR, 2025)

TULIP: Towards Unified Language-Image Pretraining. - Zineng Tang; Long Lian; Seun Eisape; Xudong Wang 007; Roei Herzig; Adam Yala; Alane Suhr; Trevor Darrell; David M. Chan (CoRR, 2025)

Higher-Order Binding of Language Model Virtual Personas: a Study on Approximating Political Partisan Misperceptions. - Minwoo Kang; Suhong Moon; Seungyong Lee 001; Ayush Raj; Joseph Suh; David M. Chan (CoRR, 2025)

Generate, but Verify: Reducing Hallucination in Vision-Language Models with Retrospective Resampling. - Tsung-Han Wu; Heekyung Lee; Jiaxin Ge; Joseph E. Gonzalez; Trevor Darrell; David M. Chan (CoRR, 2025)

LISAT: Language-Instructed Segmentation Assistant for Satellite Imagery. - Jerome Quenum; Wen-Han Hsieh; Tsung-Han Wu; Ritwik Gupta; Trevor Darrell; David M. Chan (CoRR, 2025)

REOrdering Patches Improves Vision Models. - Declan Kutscher; David M. Chan; Yutong Bai; Trevor Darrell; Ritwik Gupta (CoRR, 2025)

Puzzled by Puzzles: When Vision-Language Models Can't Take a Hint. - Heekyung Lee; Jiaxin Ge; Tsung-Han Wu; Minwoo Kang; Trevor Darrell; David M. Chan (CoRR, 2025)