collaborators

32 papers

cs.AI2026

Certified Multi-Turn Robustness for LLM Safety via Compositional Bounds and Safety Persistence

Yang Liu, Bin Chong, Wenkai Yang +9

Large language models (LLMs) are vulnerable to multi-turn jailbreak attacks that progressively manipulate conversation context. Existing certified robustness methods are limited to…

cs.CL2026

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling

Changze Lv, Zhenghua Wang, Yiran Ding +9

Large Language Models (LLMs) still struggle with the ``lost-in-the-middle'' problem, where critical information located in the middle of long-context inputs is often underrepresent…

q-bio.BM2026

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model

Changze Lv, Jiang Zhou, Siyu Long +22

We introduce AMix-1, a powerful protein foundation model built on Bayesian Flow Networks and empowered by a systematic training methodology, encompassing pretraining scaling laws,…

cs.CL2026

Learning Query-Specific Rubrics from Human Preferences for DeepResearch Report Generation

Changze Lv, Jie Zhou, Wentao Zhao +12

Nowadays, developing reliable DeepResearch-style long-form report generation remains challenging, as training and evaluation lack verifiable reward signals. Accordingly, rubric-bas…

q-bio.BM2026

AMix-2: Establishing Protein as a Native Modality in Large Language Models

Keyue Qiu, Yixin Wu, Lihao Wang +19

We present AMix-2, a protein-text foundation model that establishes protein as a native modality in large language models (LLMs), unifying protein understanding and sequence design…

cs.AI2026

From Static Context to Calibrated Interactive RL: Mitigating Distribution Shift in Multi-turn Dialogue with Aligned Simulator

Xiaohua Wang, Jiakang Yuan, Zisu Huang +5

A long-standing goal of the research community is to develop highly interactive LLM-based dialogue agents. Recent research focuses on optimizing policies based on fixed offline log…