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2020 – today
- 2024
[c23]David M. Chan, Yiming Ni, David A. Ross, Sudheendra Vijayanarasimhan, Austin Myers, John F. Canny:
Distribution Aware Metrics for Conditional Natural Language Generation. LREC/COLING 2024: 5064-5095- [c22]Yash Jain, David M. Chan, Pranav Dheram, Aparna Khare, Olabanji Shonibare, Venkatesh Ravichandran, Shalini Ghosh:
Multi-Stage Multi-Modal Pre-Training for Automatic Speech Recognition. LREC/COLING 2024: 11969-11980 - [c21]Tsung-Han Wu, Giscard Biamby, David M. Chan, Lisa Dunlap, Ritwik Gupta, Xudong Wang, Joseph E. Gonzalez, Trevor Darrell:
See, Say, and Segment: Teaching LMMs to Overcome False Premises. CVPR 2024: 13459-13469 - [c20]Suhong Moon, Marwa Abdulhai, Minwoo Kang, Joseph Suh, Widyadewi Soedarmadji, Eran Kohen Behar, David M. Chan:
Virtual Personas for Language Models via an Anthology of Backstories. EMNLP 2024: 19864-19897 - [c19]Anirudh S. Sundar, Chao-Han Huck Yang, David M. Chan, Shalini Ghosh, Venkatesh Ravichandran, Phani Sankar Nidadavolu:
Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification. ICASSP Workshops 2024: 655-659 - [c18]Kevin Cai, Chonghua Liu, David M. Chan:
Anim-400K: A Large-Scale Dataset for Automated End to End Dubbing of Video. ICASSP 2024: 11796-11800 - [c17]David M. Chan, Shalini Ghosh, Hitesh Tulsiani, Ariya Rastrow, Björn Hoffmeister:
Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition. ICASSP 2024: 11806-11810 - [c16]Hitesh Tulsiani, David M. Chan, Shalini Ghosh, Garima Lalwani, Prabhat Pandey, Ankish Bansal, Sri Garimella, Ariya Rastrow, Björn Hoffmeister:
An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems. ICML 2024 - [c15]Suzanne Petryk, David M. Chan, Anish Kachinthaya, Haodi Zou, John F. Canny, Joseph Gonzalez, Trevor Darrell:
ALOHa: A New Measure for Hallucination in Captioning Models. NAACL (Short Papers) 2024: 342-357 - [i26]David M. Chan, Shalini Ghosh, Hitesh Tulsiani, Ariya Rastrow, Björn Hoffmeister:
Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition. CoRR abs/2401.02417 (2024) - [i25]Kevin Cai, Chonghua Liu, David M. Chan:
ANIM-400K: A Large-Scale Dataset for Automated End-To-End Dubbing of Video. CoRR abs/2401.05314 (2024) - [i24]Suzanne Petryk, David M. Chan, Anish Kachinthaya, Haodi Zou, John F. Canny, Joseph E. Gonzalez, Trevor Darrell:
ALOHa: A New Measure for Hallucination in Captioning Models. CoRR abs/2404.02904 (2024) - [i23]Suhong Moon, Marwa Abdulhai, Minwoo Kang, Joseph Suh, Widyadewi Soedarmadji, Eran Kohen Behar, David M. Chan:
Virtual Personas for Language Models via an Anthology of Backstories. CoRR abs/2407.06576 (2024) - [i22]Tsung-Han Wu, Giscard Biamby, Jerome Quenum, Ritwik Gupta, Joseph E. Gonzalez, Trevor Darrell, David M. Chan:
Visual Haystacks: Answering Harder Questions About Sets of Images. CoRR abs/2407.13766 (2024) - [i21]Joseph Suh, Suhong Moon, Minwoo Kang, David M. Chan:
Rediscovering the Latent Dimensions of Personality with Large Language Models as Trait Descriptors. CoRR abs/2409.09905 (2024) - [i20]Hitesh Tulsiani, David M. Chan, Shalini Ghosh, Garima Lalwani, Prabhat Pandey, Ankish Bansal, Sri Garimella, Ariya Rastrow, Björn Hoffmeister:
An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems. CoRR abs/2409.10515 (2024) - [i19]Tsung-Han Wu, Joseph E. Gonzalez, Trevor Darrell, David M. Chan:
CLAIR-A: Leveraging Large Language Models to Judge Audio Captions. CoRR abs/2409.12962 (2024) - 2023
- [c14]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:
Towards Understanding How Machines Can Learn Causal Overhypotheses. CogSci 2023 - [c13]David M. Chan, Suzanne Petryk, Joseph Gonzalez, Trevor Darrell, John F. Canny:
CLAIR: Evaluating Image Captions with Large Language Models. EMNLP 2023: 13638-13646 - [c12]David M. Chan, Shalini Ghosh, Ariya Rastrow, Björn Hoffmeister:
Domain Adaptation with External Off-Policy Acoustic Catalogs for Scalable Contextual End-to-End Automated Speech Recognition. ICASSP 2023: 1-5 - [i18]David M. Chan, Shalini Ghosh, Ariya Rastrow, Björn Hoffmeister:
Using External Off-Policy Speech-To-Text Mappings in Contextual End-To-End Automated Speech Recognition. CoRR abs/2301.02736 (2023) - [i17]David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny:
IC3: Image Captioning by Committee Consensus. CoRR abs/2302.01328 (2023) - [i16]David M. Chan, Suzanne Petryk, Joseph E. Gonzalez, Trevor Darrell, John F. Canny:
CLAIR: Evaluating Image Captions with Large Language Models. CoRR abs/2310.12971 (2023) - [i15]Tsung-Han Wu, Giscard Biamby, David M. Chan, Lisa Dunlap, Ritwik Gupta, Xudong Wang, Joseph E. Gonzalez, Trevor Darrell:
See, Say, and Segment: Teaching LMMs to Overcome False Premises. CoRR abs/2312.08366 (2023) - [i14]Anirudh S. Sundar, Chao-Han Huck Yang, David M. Chan, Shalini Ghosh, Venkatesh Ravichandran, Phani Sankar Nidadavolu:
Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification. CoRR abs/2312.14378 (2023) - 2022
- [c11]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:
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CLeaR 2022: 390-406 - [c10]Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Bryanna Kaufmann, Alison Gopnik:
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CogSci 2022 - [c9]David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, Bryan Seybold, John F. Canny:
What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics. CVPR Workshops 2022: 4739-4748 - [c8]David M. Chan, Shalini Ghosh, Debmalya Chakrabarty, Björn Hoffmeister:
Multi-Modal Pre-Training for Automated Speech Recognition. ICASSP 2022: 246-250 - [c7]David M. Chan, Shalini Ghosh:
Content-Context Factorized Representations for Automated Speech Recognition. INTERSPEECH 2022: 61-65 - [i13]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:
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CoRR abs/2202.10430 (2022) - [i12]David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, Bryan Seybold, John F. Canny:
What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics. CoRR abs/2205.06253 (2022) - [i11]David M. Chan, Shalini Ghosh:
Content-Context Factorized Representations for Automated Speech Recognition. CoRR abs/2205.09872 (2022) - [i10]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:
Towards Understanding How Machines Can Learn Causal Overhypotheses. CoRR abs/2206.08353 (2022) - [i9]David M. Chan, Yiming Ni, David A. Ross, Sudheendra Vijayanarasimhan, Austin Myers, John F. Canny:
Distribution Aware Metrics for Conditional Natural Language Generation. CoRR abs/2209.07518 (2022) - 2021
- [i8]Aatif Jiwani, Shubhrakanti Ganguly, Chao Ding, Nan Zhou, David M. Chan:
A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery. CoRR abs/2104.01263 (2021) - [i7]David M. Chan, Shalini Ghosh, Debmalya Chakrabarty, Björn Hoffmeister:
Multi-Modal Pre-Training for Automated Speech Recognition. CoRR abs/2110.09890 (2021) - 2020
- [c6]David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny:
Active Learning for Video Description with Cluster-Regularized Ensemble Ranking. ACCV (5) 2020: 443-459 - [c5]Eliza Kosoy, Jasmine Collins, David M. Chan, Deepak Pathak, Pulkit Agrawal, Alison Gopnik:
Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. CogSci 2020 - [i6]Eliza Kosoy, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy H. Huang, Alison Gopnik, John F. Canny:
Exploring Exploration: Comparing Children with RL Agents in Unified Environments. CoRR abs/2005.02880 (2020) - [i5]Bofan Xue, David M. Chan, John F. Canny:
A Dataset and Benchmarks for Multimedia Social Analysis. CoRR abs/2006.08335 (2020) - [i4]David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny:
Active Learning for Video Description With Cluster-Regularized Ensemble Ranking. CoRR abs/2007.13913 (2020)
2010 – 2019
- 2019
- [j2]David M. Chan, Roshan Rao, Forrest Huang, John F. Canny:
GPU accelerated t-distributed stochastic neighbor embedding. J. Parallel Distributed Comput. 131: 1-13 (2019) - [i3]Daniel Seita, David M. Chan, Roshan Rao, Chen Tang, Mandi Zhao, John F. Canny:
ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations. CoRR abs/1910.12154 (2019) - 2018
- [c4]Liron Cohen, Sven Koenig, T. K. Satish Kumar, Glenn Wagner, Howie Choset, David M. Chan, Nathan R. Sturtevant:
Rapid Randomized Restarts for Multi-Agent Path Finding: Preliminary Results. AAMAS 2018: 1909-1911 - [c3]David M. Chan, Roshan Rao, Forrest Huang, John F. Canny:
T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data. SBAC-PAD 2018: 330-338 - [c2]Liron Cohen, Glenn Wagner, David M. Chan, Howie Choset, Nathan R. Sturtevant, Sven Koenig, T. K. Satish Kumar:
Rapid Randomized Restarts for Multi-Agent Path Finding Solvers. SOCS 2018: 148-152 - [i2]David M. Chan, Roshan Rao, Forrest Huang, John F. Canny:
t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern Data. CoRR abs/1807.11824 (2018) - [i1]Biye Jiang, David M. Chan, Tianhao Zhang, John F. Canny:
Diagnostic Visualization for Deep Neural Networks Using Stochastic Gradient Langevin Dynamics. CoRR abs/1812.04604 (2018) - 2017
- [c1]Thayne T. Walker, David M. Chan, Nathan R. Sturtevant:
Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding. ICAPS 2017: 316-324
2000 – 2009
- 2004
- [j1]David M. Chan, John E. Franke:
Probabilities of extinction, weak extinction, permanence, and mutual exclusion in discrete, competitive, Lotka-Volterra systems that involve invading species. Math. Comput. Model. 40(7-8): 809-821 (2004)
Coauthor Index
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