David M. Chan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
27
Venues
15
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
27 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | Enough Coin Flips Can Make LLMs Act Bayesian. | Ritwik Gupta, Rodolfo Corona, Jiaxin Ge, Eric Wang, Dan Klein, Trevor Darrell, David M. Chan |
| 2025 | ASRU | Analysing the Language of Neural Audio Codecs. | Joonyong Park, Shinnosuke Takamichi, David M. Chan, Shunsuke Kando, Yuki Saito, Hiroshi Saruwatari |
| 2025 | ASRU | CLAIRA: Leveraging Large Language Models to Judge Audio Captions. | Tsung-Han Wu, Joseph E. Gonzalez, Trevor Darrell, David M. Chan |
| 2025 | EMNLP | Do What? Teaching Vision-Language-Action Models to Reject the Impossible. | Wen-Han Hsieh, Elvis Hsieh, Dantong Niu, Trevor Darrell, Roei Herzig, David M. Chan |
| 2025 | EMNLP | 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 |
| 2025 | ICCV | TULIP: Contrastive Image-Text Learning with Richer Vision Understanding. | Zineng Tang, Long Lian, Seun Eisape, Xudong Wang, Roei Herzig, Adam Yala, Alane Suhr, Trevor Darrell, David M. Chan |
| 2025 | ICLR | 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 |
| 2024 | COLING | Distribution Aware Metrics for Conditional Natural Language Generation. | David M. Chan, Yiming Ni, David A. Ross, Sudheendra Vijayanarasimhan, Austin Myers, John F. Canny |
| 2024 | COLING | 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 |
| 2024 | CVPR | See, Say, and Segment: Teaching LMMs to Overcome False Premises. | Tsung-Han Wu, Giscard Biamby, David M. Chan, Lisa Dunlap, Ritwik Gupta, Xudong Wang, Joseph E. Gonzalez, Trevor Darrell |
| 2024 | EMNLP | 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 |
| 2024 | ICASSP | Anim-400K: A Large-Scale Dataset for Automated End to End Dubbing of Video. | Kevin Cai, Chonghua Liu, David M. Chan |
| 2024 | ICASSP | Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition. | David M. Chan, Shalini Ghosh, Hitesh Tulsiani, Ariya Rastrow, Bjrn Hoffmeister |
| 2024 | ICASSP | 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 |
| 2024 | ICML | 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, Bjrn Hoffmeister |
| 2024 | NAACL | ALOHa: A New Measure for Hallucination in Captioning Models. | Suzanne Petryk, David M. Chan, Anish Kachinthaya, Haodi Zou, John F. Canny, Joseph Gonzalez, Trevor Darrell |
| 2023 | CogSci | 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 |
| 2023 | EMNLP | CLAIR: Evaluating Image Captions with Large Language Models. | David M. Chan, Suzanne Petryk, Joseph Gonzalez, Trevor Darrell, John F. Canny |
| 2023 | ICASSP | Domain Adaptation with External Off-Policy Acoustic Catalogs for Scalable Contextual End-to-End Automated Speech Recognition. | David M. Chan, Shalini Ghosh, Ariya Rastrow, Bjrn Hoffmeister |
| 2022 | CogSci | 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 |
| 2022 | CVPR | 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 |
| 2022 | ICASSP | Multi-Modal Pre-Training for Automated Speech Recognition. | David M. Chan, Shalini Ghosh, Debmalya Chakrabarty, Bjrn Hoffmeister |
| 2022 | Interspeech | Content-Context Factorized Representations for Automated Speech Recognition. | David M. Chan, Shalini Ghosh |
| 2020 | ACCV | Active Learning for Video Description with Cluster-Regularized Ensemble Ranking. | David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny |
| 2020 | CogSci | Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. | Eliza Kosoy, Jasmine Collins, David M. Chan, Deepak Pathak, Pulkit Agrawal, Alison Gopnik |
| 2018 | SBAC-PAD | T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data. | David M. Chan, Roshan Rao, Forrest Huang, John F. Canny |
| 2018 | SoCS | Rapid Randomized Restarts for Multi-Agent Path Finding Solvers. | Liron Cohen, Glenn Wagner, David M. Chan, Howie Choset, Nathan R. Sturtevant, Sven Koenig, T. K. Satish Kumar |