Justin Chih-Yao Chen

According to our database, Justin Chih-Yao Chen authored at least 18 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

GPU Forecasters: Language Models as Selective Surrogates for Kernel Runtime Optimization.

Zaid Khan, Justin Chih-Yao Chen, Jaemin Cho, Elias Stengel-Eskin, Mohit Bansal

CoRR, May, 2026

MINTEval: Evaluating Memory under Multi-Target Interference in Long-Horizon Agent Systems.

Hyunji Lee, Justin Chih-Yao Chen, Joykirat Singh, Zaid Khan, Elias Stengel-Eskin, Mohit Bansal

CoRR, May, 2026

Agent-BRACE: Decoupling Beliefs from Actions in Long-Horizon Tasks via Verbalized State Uncertainty.

Joykirat Singh, Zaid Khan, Archiki Prasad, Justin Chih-Yao Chen, Akshay Nambi, Hyunji Lee, Elias Stengel-Eskin, Mohit Bansal

CoRR, May, 2026

Cog-DRIFT: Exploration on Adaptively Reformulated Instances Enables Learning from Hard Reasoning Problems.

Justin Chih-Yao Chen, Archiki Prasad, Zaid Khan, Joykirat Singh, Runchu Tian, Elias Stengel-Eskin, Mohit Bansal

CoRR, April, 2026

DART: Leveraging Multi-Agent Disagreement for Tool Recruitment in Multimodal Reasoning.

Nithin Sivakumaran, Justin Chih-Yao Chen, David Wan, Yue Zhang, Jaehong Yoon, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

Routing with Generated Data: Annotation-Free LLM Skill Estimation and Expert Selection.

Tianyi Niu, Justin Chih-Yao Chen, Genta Indra Winata, Shi-Xiong Zhang, Supriyo Chakraborty, Sambit Sahu, Yue Zhang, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

PRInTS: Reward Modeling for Long-Horizon Information Seeking.

Jaewoo Lee, Archiki Prasad, Justin Chih-Yao Chen, Zaid Khan, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

Think Right: Learning to Mitigate Under-Over Thinking via Adaptive, Attentive Compression.

Joykirat Singh, Justin Chih-Yao Chen, Archiki Prasad, Elias Stengel-Eskin, Akshay Nambi, Mohit Bansal

CoRR, October, 2025

Nudging the Boundaries of LLM Reasoning.

Justin Chih-Yao Chen, Becky Xiangyu Peng, Prafulla Kumar Choubey, Kung-Hsiang Huang, Jiaxin Zhang, Mohit Bansal, Chien-Sheng Wu

CoRR, September, 2025

Symbolic Mixture-of-Experts: Adaptive Skill-based Routing for Heterogeneous Reasoning.

Justin Chih-Yao Chen, Sukwon Yun, Elias Stengel-Eskin, Tianlong Chen, Mohit Bansal

CoRR, March, 2025

Learning to Generate Unit Tests for Automated Debugging.

Archiki Prasad, Elias Stengel-Eskin, Justin Chih-Yao Chen, Zaid Khan, Mohit Bansal

CoRR, February, 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

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Reverse Thinking Makes LLMs Stronger Reasoners.

Justin Chih-Yao Chen, Zifeng Wang, Hamid Palangi, Rujun Han, Sayna Ebrahimi, Long T. Le, Vincent Perot, Swaroop Mishra, Mohit Bansal, Chen-Yu Lee, Tomas Pfister

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning.

Justin Chih-Yao Chen, Archiki Prasad, Swarnadeep Saha, Elias Stengel-Eskin, Mohit Bansal

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs.

Justin Chih-Yao Chen, Swarnadeep Saha, Mohit Bansal

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

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

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023