Location-Aware Visual Question Generation with Lightweight Models. - Nicholas Collin Suwono; Justin Chih-Yao Chen; Tun-Min Hung; Ting-Hao (Kenneth) Huang; I-Bin Liao; Yung-Hui Li; Lun-Wei Ku; Shao-Hua Sun (EMNLP, 2023)

ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs. - Justin Chih-Yao Chen; Swarnadeep Saha; Mohit Bansal (ACL (1), 2024)

MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models. - Justin Chih-Yao Chen; Swarnadeep Saha; Elias Stengel-Eskin; Mohit Bansal (ICML, 2024)

MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning. - Justin Chih-Yao Chen; Archiki Prasad; Swarnadeep Saha; Elias Stengel-Eskin; Mohit Bansal (CoRR, 2024)

System 1.x: Learning to Balance Fast and Slow Planning with Language Models. - Swarnadeep Saha; Archiki Prasad; Justin Chih-Yao Chen; Peter Hase; Elias Stengel-Eskin; Mohit Bansal (ICLR, 2025)

Reverse Thinking Makes LLMs Stronger Reasoners. - Justin Chih-Yao Chen; Zifeng Wang 002; Hamid Palangi; Rujun Han; Sayna Ebrahimi; Long T. Le; Vincent Perot; Swaroop Mishra; Mohit Bansal; Chen-Yu Lee; Tomas Pfister (NAACL (Long Papers), 2025)

MAMM-Refine: A Recipe for Improving Faithfulness in Generation with Multi-Agent Collaboration. - David Wan; Justin Chih-Yao Chen; Elias Stengel-Eskin; Mohit Bansal (NAACL (Long Papers), 2025)

Learning to Generate Unit Tests for Automated Debugging. - Archiki Prasad; Elias Stengel-Eskin; Justin Chih-Yao Chen; Zaid Khan 001; Mohit Bansal (CoRR, 2025)

Symbolic Mixture-of-Experts: Adaptive Skill-based Routing for Heterogeneous Reasoning. - Justin Chih-Yao Chen; Sukwon Yun; Elias Stengel-Eskin; Tianlong Chen 001; Mohit Bansal (CoRR, 2025)