David M. Chan - RankMe

72 papers A* 7A 2B 4C 3Misc 4Journal 42Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Attend Before Attention: Efficient and Scalable Video Understanding via Autoregressive Gazing. CoRR Baifeng Shi, Stephanie Fu, Long Lian, Hanrong Ye, David Eigen, Aaron Reite, Boyi Li, Jan Kautz, Song Han, David M. Chan, Pavlo Molchanov, Trevor Darrell, Hongxu Yin
2026	J	`jnl`	VisGym: Diverse, Customizable, Scalable Environments for Multimodal Agents. CoRR Zirui Wang, Junyi Zhang, Jiaxin Ge, Long Lian, Letian Fu, Lisa Dunlap, Ken Goldberg, Xudong Wang, Ion Stoica, David M. Chan, Sewon Min, Joseph E. Gonzalez
2025	C	`conf`	Analysing the Language of Neural Audio Codecs. ASRU Joonyong Park, Shinnosuke Takamichi, David M. Chan, Shunsuke Kando, Yuki Saito, Hiroshi Saruwatari
2025	J	`jnl`	Analysing the Language of Neural Audio Codecs. CoRR Joonyong Park, Shinnosuke Takamichi, David M. Chan, Shunsuke Kando, Yuki Saito, Hiroshi Saruwatari
2025	J	`jnl`	Are Large Reasoning Models Interruptible? CoRR Tsung-Han Wu, Mihran Miroyan, David M. Chan, Trevor Darrell, Narges Norouzi, Joseph E. Gonzalez
2025	C	`conf`	CLAIRA: Leveraging Large Language Models to Judge Audio Captions. ASRU Tsung-Han Wu, Joseph E. Gonzalez, Trevor Darrell, David M. Chan
2025	J	`jnl`	Constantly Improving Image Models Need Constantly Improving Benchmarks. CoRR Jiaxin Ge, Grace Luo, Heekyung Lee, Nishant Malpani, Long Lian, Xudong Wang, Aleksander Holynski, Trevor Darrell, Sewon Min, David M. Chan
2025	—	`conf`	Do What? Teaching Vision-Language-Action Models to Reject the Impossible. EMNLP (Findings) Wen-Han Hsieh, Elvis Hsieh, Dantong Niu, Trevor Darrell, Roei Herzig, David M. Chan
2025	J	`jnl`	Do What? Teaching Vision-Language-Action Models to Reject the Impossible. CoRR Wen-Han Hsieh, Elvis Hsieh, Dantong Niu, Trevor Darrell, Roei Herzig, David M. Chan
2025	—	`conf`	Enough Coin Flips Can Make LLMs Act Bayesian. ACL (1) Ritwik Gupta, Rodolfo Corona, Jiaxin Ge, Eric Wang, Dan Klein, Trevor Darrell, David M. Chan
2025	J	`jnl`	Enough Coin Flips Can Make LLMs Act Bayesian. CoRR Ritwik Gupta, Rodolfo Corona, Jiaxin Ge, Eric Wang, Dan Klein, Trevor Darrell, David M. Chan
2025	J	`jnl`	Generate, but Verify: Reducing Hallucination in Vision-Language Models with Retrospective Resampling. CoRR Tsung-Han Wu, Heekyung Lee, Jiaxin Ge, Joseph E. Gonzalez, Trevor Darrell, David M. Chan
2025	J	`jnl`	Higher-Order Binding of Language Model Virtual Personas: a Study on Approximating Political Partisan Misperceptions. CoRR Minwoo Kang, Suhong Moon, Seungyong Lee, Ayush Raj, Joseph Suh, David M. Chan
2025	J	`jnl`	LISAT: Language-Instructed Segmentation Assistant for Satellite Imagery. CoRR Jerome Quenum, Wen-Han Hsieh, Tsung-Han Wu, Ritwik Gupta, Trevor Darrell, David M. Chan
2025	A*	`conf`	Puzzled by Puzzles: When Vision-Language Models Can't Take a Hint. EMNLP Heekyung Lee, Jiaxin Ge, Tsung-Han Wu, Minwoo Kang, Trevor Darrell, David M. Chan
2025	J	`jnl`	Puzzled by Puzzles: When Vision-Language Models Can't Take a Hint. CoRR Heekyung Lee, Jiaxin Ge, Tsung-Han Wu, Minwoo Kang, Trevor Darrell, David M. Chan
2025	J	`jnl`	REOrdering Patches Improves Vision Models. CoRR Declan Kutscher, David M. Chan, Yutong Bai, Trevor Darrell, Ritwik Gupta
2025	—	`conf`	TULIP: Contrastive Image-Text Learning with Richer Vision Understanding. ICCVW Zineng Tang, Long Lian, Seun Eisape, Xudong Wang, Roei Herzig, Adam Yala, Alane Suhr, Trevor Darrell, David M. Chan
2025	J	`jnl`	TULIP: Towards Unified Language-Image Pretraining. CoRR Zineng Tang, Long Lian, Seun Eisape, Xudong Wang, Roei Herzig, Adam Yala, Alane Suhr, Trevor Darrell, David M. Chan
2025	A*	`conf`	Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark. ICLR Tsung-Han Wu, Giscard Biamby, Jerome Quenum, Ritwik Gupta, Joseph E. Gonzalez, Trevor Darrell, David M. Chan
2024	—	`conf`	ALOHa: A New Measure for Hallucination in Captioning Models. NAACL (Short Papers) Suzanne Petryk, David M. Chan, Anish Kachinthaya, Haodi Zou, John F. Canny, Joseph Gonzalez, Trevor Darrell
2024	J	`jnl`	ALOHa: A New Measure for Hallucination in Captioning Models. CoRR Suzanne Petryk, David M. Chan, Anish Kachinthaya, Haodi Zou, John F. Canny, Joseph E. Gonzalez, Trevor Darrell
2024	J	`jnl`	ANIM-400K: A Large-Scale Dataset for Automated End-To-End Dubbing of Video. CoRR Kevin Cai, Chonghua Liu, David M. Chan
2024	A*	`conf`	An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems. ICML Hitesh Tulsiani, David M. Chan, Shalini Ghosh, Garima Lalwani, Prabhat Pandey, Ankish Bansal, Sri Garimella, Ariya Rastrow, Björn Hoffmeister
2024	J	`jnl`	An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems. CoRR Hitesh Tulsiani, David M. Chan, Shalini Ghosh, Garima Lalwani, Prabhat Pandey, Ankish Bansal, Sri Garimella, Ariya Rastrow, Björn Hoffmeister
2024	J	`jnl`	Analyzing The Language of Visual Tokens. CoRR David M. Chan, Rodolfo Corona, Joonyong Park, Cheol Jun Cho, Yutong Bai, Trevor Darrell
2024	Misc	`conf`	Anim-400K: A Large-Scale Dataset for Automated End to End Dubbing of Video. ICASSP Kevin Cai, Chonghua Liu, David M. Chan
2024	J	`jnl`	CLAIR-A: Leveraging Large Language Models to Judge Audio Captions. CoRR Tsung-Han Wu, Joseph E. Gonzalez, Trevor Darrell, David M. Chan
2024	—	`conf`	Distribution Aware Metrics for Conditional Natural Language Generation. LREC/COLING David M. Chan, Yiming Ni, David A. Ross, Sudheendra Vijayanarasimhan, Austin Myers, John F. Canny
2024	—	`conf`	Multi-Stage Multi-Modal Pre-Training for Automatic Speech Recognition. LREC/COLING Yash Jain, David M. Chan, Pranav Dheram, Aparna Khare, Olabanji Shonibare, Venkatesh Ravichandran, Shalini Ghosh
2024	—	`conf`	Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification. ICASSP Workshops Anirudh S. Sundar, Chao-Han Huck Yang, David M. Chan, Shalini Ghosh, Venkatesh Ravichandran, Phani Sankar Nidadavolu
2024	J	`jnl`	Rediscovering the Latent Dimensions of Personality with Large Language Models as Trait Descriptors. CoRR Joseph Suh, Suhong Moon, Minwoo Kang, David M. Chan
2024	A*	`conf`	See, Say, and Segment: Teaching LMMs to Overcome False Premises. CVPR Tsung-Han Wu, Giscard Biamby, David M. Chan, Lisa Dunlap, Ritwik Gupta, Xudong Wang, Joseph E. Gonzalez, Trevor Darrell
2024	Misc	`conf`	Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition. ICASSP David M. Chan, Shalini Ghosh, Hitesh Tulsiani, Ariya Rastrow, Björn Hoffmeister
2024	J	`jnl`	Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition. CoRR David M. Chan, Shalini Ghosh, Hitesh Tulsiani, Ariya Rastrow, Björn Hoffmeister
2024	A*	`conf`	Virtual Personas for Language Models via an Anthology of Backstories. EMNLP Suhong Moon, Marwa Abdulhai, Minwoo Kang, Joseph Suh, Widyadewi Soedarmadji, Eran Kohen Behar, David M. Chan
2024	J	`jnl`	Virtual Personas for Language Models via an Anthology of Backstories. CoRR Suhong Moon, Marwa Abdulhai, Minwoo Kang, Joseph Suh, Widyadewi Soedarmadji, Eran Kohen Behar, David M. Chan
2024	J	`jnl`	Visual Haystacks: Answering Harder Questions About Sets of Images. CoRR Tsung-Han Wu, Giscard Biamby, Jerome Quenum, Ritwik Gupta, Joseph E. Gonzalez, Trevor Darrell, David M. Chan
2023	A*	`conf`	CLAIR: Evaluating Image Captions with Large Language Models. EMNLP David M. Chan, Suzanne Petryk, Joseph Gonzalez, Trevor Darrell, John F. Canny
2023	J	`jnl`	CLAIR: Evaluating Image Captions with Large Language Models. CoRR David M. Chan, Suzanne Petryk, Joseph E. Gonzalez, Trevor Darrell, John F. Canny
2023	Misc	`conf`	Domain Adaptation with External Off-Policy Acoustic Catalogs for Scalable Contextual End-to-End Automated Speech Recognition. ICASSP David M. Chan, Shalini Ghosh, Ariya Rastrow, Björn Hoffmeister
2023	J	`jnl`	IC CoRR David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny
2023	J	`jnl`	Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification. CoRR Anirudh S. Sundar, Chao-Han Huck Yang, David M. Chan, Shalini Ghosh, Venkatesh Ravichandran, Phani Sankar Nidadavolu
2023	J	`jnl`	See, Say, and Segment: Teaching LMMs to Overcome False Premises. CoRR Tsung-Han Wu, Giscard Biamby, David M. Chan, Lisa Dunlap, Ritwik Gupta, Xudong Wang, Joseph E. Gonzalez, Trevor Darrell
2023	B	`conf`	Towards Understanding How Machines Can Learn Causal Overhypotheses. CogSci 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
2023	J	`jnl`	Using External Off-Policy Speech-To-Text Mappings in Contextual End-To-End Automated Speech Recognition. CoRR David M. Chan, Shalini Ghosh, Ariya Rastrow, Björn Hoffmeister
2022	A	`conf`	Content-Context Factorized Representations for Automated Speech Recognition. INTERSPEECH David M. Chan, Shalini Ghosh
2022	J	`jnl`	Content-Context Factorized Representations for Automated Speech Recognition. CoRR David M. Chan, Shalini Ghosh
2022	J	`jnl`	Distribution Aware Metrics for Conditional Natural Language Generation. CoRR David M. Chan, Yiming Ni, David A. Ross, Sudheendra Vijayanarasimhan, Austin Myers, John F. Canny
2022	—	`conf`	Learning Causal Overhypotheses through Exploration in Children and Computational Models. CLeaR 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
2022	B	`conf`	Learning Causal Overhypotheses through Exploration in Children and Computational Models. CogSci Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Bryanna Kaufmann, Alison Gopnik
2022	J	`jnl`	Learning Causal Overhypotheses through Exploration in Children and Computational Models. CoRR 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
2022	Misc	`conf`	Multi-Modal Pre-Training for Automated Speech Recognition. ICASSP David M. Chan, Shalini Ghosh, Debmalya Chakrabarty, Björn Hoffmeister
2022	J	`jnl`	Towards Understanding How Machines Can Learn Causal Overhypotheses. CoRR 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
2022	—	`conf`	What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics. CVPR Workshops David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, Bryan Seybold, John F. Canny
2022	J	`jnl`	What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics. CoRR David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, Bryan Seybold, John F. Canny
2021	J	`jnl`	A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery. CoRR Aatif Jiwani, Shubhrakanti Ganguly, Chao Ding, Nan Zhou, David M. Chan
2021	J	`jnl`	Multi-Modal Pre-Training for Automated Speech Recognition. CoRR David M. Chan, Shalini Ghosh, Debmalya Chakrabarty, Björn Hoffmeister
2020	J	`jnl`	A Dataset and Benchmarks for Multimedia Social Analysis. CoRR Bofan Xue, David M. Chan, John F. Canny
2020	J	`jnl`	Active Learning for Video Description With Cluster-Regularized Ensemble Ranking. CoRR David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny
2020	—	`conf`	Active Learning for Video Description with Cluster-Regularized Ensemble Ranking. ACCV (5) David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny
2020	B	`conf`	Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. CogSci Eliza Kosoy, Jasmine Collins, David M. Chan, Deepak Pathak, Pulkit Agrawal, Alison Gopnik
2020	J	`jnl`	Exploring Exploration: Comparing Children with RL Agents in Unified Environments. CoRR Eliza Kosoy, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy H. Huang, Alison Gopnik, John F. Canny
2019	J	`jnl`	GPU accelerated t-distributed stochastic neighbor embedding. J. Parallel Distributed Comput. David M. Chan, Roshan Rao, Forrest Huang, John F. Canny
2019	J	`jnl`	ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations. CoRR Daniel Seita, David M. Chan, Roshan Rao, Chen Tang, Mandi Zhao, John F. Canny
2018	J	`jnl`	Diagnostic Visualization for Deep Neural Networks Using Stochastic Gradient Langevin Dynamics. CoRR Biye Jiang, David M. Chan, Tianhao Zhang, John F. Canny
2018	B	`conf`	Rapid Randomized Restarts for Multi-Agent Path Finding Solvers. SOCS Liron Cohen, Glenn Wagner, David M. Chan, Howie Choset, Nathan R. Sturtevant, Sven Koenig, T. K. Satish Kumar
2018	A	`conf`	Rapid Randomized Restarts for Multi-Agent Path Finding: Preliminary Results. AAMAS Liron Cohen, Sven Koenig, T. K. Satish Kumar, Glenn Wagner, Howie Choset, David M. Chan, Nathan R. Sturtevant
2018	C	`conf`	T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data. SBAC-PAD David M. Chan, Roshan Rao, Forrest Huang, John F. Canny
2018	J	`jnl`	t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern Data. CoRR David M. Chan, Roshan Rao, Forrest Huang, John F. Canny
2017	A*	`conf`	Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding. ICAPS Thayne T. Walker, David M. Chan, Nathan R. Sturtevant
2004	J	`jnl`	Probabilities of extinction, weak extinction, permanence, and mutual exclusion in discrete, competitive, Lotka-Volterra systems that involve invading species. Math. Comput. Model. David M. Chan, John E. Franke