collaborators

17 papers

cs.AI2026

SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection

Zhiyong Cao, Dunqiang Liu, Qi Dai +9

Task-oriented proactive dialogue agents play a pivotal role in recruitment, particularly for steering conversations towards specific business outcomes, such as acquiring social-med…

cs.LG2026

How Data Shapes RoPE Frequency Usage: From Positional Scale Matching to Length Generalization

Xinyi Wu, Siyuan Liu, Ali Jadbabaie

Rotary Position Embeddings (RoPE) provide transformers with a fixed grid of positional frequencies, yet trained models use these frequencies highly non-uniformly. We study what det…

cs.AI2026

Late-Layer Fusion is Enough: Dual-Path Vision Token Routing for Multimodal Large Language Models under Visual Saturation

Siyuan Liu, Jinyang Wu

Multimodal large language models (MLLMs) commonly inherit the deep, symmetric Transformer backbone designed for unimodal text modeling, and apply the same computation uniformly to…

cs.CL2026

Defending Against Malicious Finetuning by Scaling Train-time Adversarial Attacks

Haoming Wen, Shi Chen, Qingyu Shi +4

Current open-weight large language models (LLMs) are prone to malicious finetuning attacks, which could compromise the safety alignment of LLMs with only a few steps of supervised…

cs.CV2026

ViCuR: Visual Cues as Recoverable Privilege for Multimodal On-Policy Distillation

Kanghui Tian, Siyuan Liu, Ziang Yan +3

On-policy distillation (OPD) improves reasoning by training a student on trajectories sampled from its own policy under supervision from a teacher. In multimodal reasoning, a commo…

cs.CL2026

OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents

Jiahao Ying, Boxian Ai, Wei Tang +2

Skills, i.e., structured workflow instructions distilled for large language models (LLMs), are becoming an increasingly important mechanism for improving agent performance on real-…