6 citations · 9 across the 17 of their papers we have counts for
7 papers · 1 filter
RARE: Decoupling Representation Steering from Expert Routing in Mixture-of-Experts Language Models
Zhibo Zhang, Zhen Ouyang, Ling Shi +1
Representation engineering offers a lightweight means of controlling language-model behavior by modifying intermediate hidden states, but its direct application to Mixture-of-Exper…
TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation
Zhibo Zhang, Zhen Ouyang, Ling Shi +1
Agent Skills package reusable natural language procedures with executable resources, enabling software agents to acquire task specific capabilities without model adaptation. Automa…
Defense Against LLM Backdoors using Critical Neuron Isolation Pruning
Yuxi Li, Zhibo Zhang, Kailong Wang +3
Large language models (LLMs) are vulnerable to backdoor attacks, where hidden triggers induce malicious outputs. Existing defenses generally fall into inference-time detection or t…
A Temporal Reasoning Benchmarking Framework for LRMs via Difficulty-controlled and Dynamic Test Generation
Shide Zhou, Kailong Wang, Ling Shi +1
Defining the reasoning boundaries and ensuring the reliability of Large Reasoning Models (LRMs) remains a critical challenge. Current benchmarks primarily rely on static datasets s…
R2IF: Aligning Reasoning with Decisions via Composite Rewards for Interpretable LLM Function Calling
Aijia Cheng, Kailong Wang, Ling Shi +1
Function calling empowers large language models (LLMs) to interface with external tools, yet existing RL-based approaches suffer from misalignment between reasoning processes and t…
RASET: Router-Agnostic Safety-Critical Expert Tuning Exposes Localized Safety Enforcement Failures in Mixture-of-Experts LLMs
Zhibo Zhang, Yuxi Li, Zhen Ouyang +2
Mixture-of-Experts (MoE) LLMs rely on sparse, router-driven expert activation, yet how safety alignment interacts with routed expert specialization remains underexplored. A common…
STEAMROLLER: A Multi-Agent System for Inclusive Automatic Speech Recognition for People who Stutter
Ziqi Xu, Yi Liu, Yuekang Li +3
People who stutter (PWS) face systemic exclusion in today's voice-driven society, where access to voice assistants, authentication systems, and remote work tools increasingly depen…