activity
20232026
most citedCalibrating LLM-Based Evaluator

3 citations · 3 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2026

RemoteShield: Enable Robust Multimodal Large Language Models for Earth Observation

Rui Min, Liang Yao, Shiyu Miao +5

A robust Multimodal Large Language Model (MLLM) for Earth Observation should maintain consistent interpretation and reasoning under realistic input variations. However, current Rem…

cs.AI2026

OOD-MMSafe: Advancing MLLM Safety from Harmful Intent to Hidden Consequences

Ming Wen, Kun Yang, Jingyu Zhang +4

While safety alignment for Multimodal Large Language Models (MLLMs) has gained significant attention, current paradigms primarily target malicious intent or situational violations.…

cs.CL2025

PEO: Improving Bi-Factorial Preference Alignment with Post-Training Policy Extrapolation

Yuxuan Liu

The alignment of large language models with human values presents a critical challenge, particularly when balancing conflicting objectives like helpfulness and harmlessness. Existi…

cs.IR2024

ASI++: Towards Distributionally Balanced End-to-End Generative Retrieval

Yuxuan Liu, Tianchi Yang, Zihan Zhang +5

Generative retrieval, a promising new paradigm in information retrieval, employs a seq2seq model to encode document features into parameters and decode relevant document identifier…

cs.CV2024

Plug-and-Play Grounding of Reasoning in Multimodal Large Language Models

Jiaxing Chen, Yuxuan Liu, Dehu Li +5

The rise of Multimodal Large Language Models (MLLMs), renowned for their advanced instruction-following and reasoning capabilities, has significantly propelled the field of visual…

cs.CL2024

HD-Eval: Aligning Large Language Model Evaluators Through Hierarchical Criteria Decomposition

Yuxuan Liu, Tianchi Yang, Shaohan Huang +6

Large language models (LLMs) have emerged as a promising alternative to expensive human evaluations. However, the alignment and coverage of LLM-based evaluations are often limited…