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Pengcheng Wen
Observed name:
Wen, Pengcheng
Institution:
Hong Kong University of Science and Technology
Observed institution:
Hong Kong University of Science and Technology
OpenAlex ID:
A5120028648
Omni-RewardBench: Toward a Comprehensive Evaluation of Generative Reward Models Across Modalities
2026
·
Association for Computational Linguistics 2026
, CHAN, CHIMIN
, et al.
·
Underline Science Inc.
SafeMT: Multi-turn Safety for Multimodal Language Models
2026
·
Association for Computational Linguistics 2026
, Cai, Chengkun
, et al.
·
Underline Science Inc.
Legal Aligner: Transforming Generic LLMs into Domain Experts for Enhanced Accuracy
2026
·
Pengcheng Wen
, Guoying LU
, et al.
·
Research Square
PDF
What, Whether and How? Unveiling Process Reward Models for Thinking with Images Reasoning
2026
·
Yujin Zhou
, Pengcheng Wen
, et al.
·
Proceedings of the AAAI Conference on Artificial Intelligence
PDF
What, Whether and How? Unveiling Process Reward Models for Thinking with Images Reasoning
2026
·
Zhou, Yujin
, Wen, Pengcheng
, et al.
·
arXiv (Cornell University)
PDF
Glance-or-Gaze: Incentivizing LMMs to Adaptively Focus Search via Reinforcement Learning
2026
·
Bai, Hongbo
, Zhou, Yujin
, et al.
·
arXiv (Cornell University)
PDF
SafeMT: Multi-turn Safety for Multimodal Language Models
2026
·
Han Zhu
, Juntao Dai
, et al.
·
Proceedings of the conference - Association for Computational Linguistics. Meeting
Towards Multi-modal Multi-turn Safety: From Agentic Interaction to Strategic Alignment
2026
·
Han Zhu
, Jiale Chen
, et al.
·
Conference on Empirical Methods in Natural Language Processing (EMNLP)
PDF
Not Just the Destination, But the Journey: Reasoning Traces Causally Shape Generalization Behaviors
2026
·
Pengcheng Wen
, Yanxu Zhu
, et al.
·
Conference on Empirical Methods in Natural Language Processing (EMNLP)
PDF
Understanding the Reasoning Process in Large (Vision-)Language Models: From Capability to Alignment
2026
·
Pengcheng Wen
Cross-Modal Emergent Misalignment Through Narrow-Domain Fine-Tuning
2026
·
Han Zhu
, Chengkun Cai
, et al.
·
Conference on Empirical Methods in Natural Language Processing (EMNLP)
PDF
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Works count:
11
Citation count:
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