activity
20242026
collaborators

7 papers

cs.LG2026

Beyond the Training Horizon: Mechanisms and Limits of Length Generalization in Looped Transformers

Jia Liang, Xi Jin, Liangming Pan

Looped Transformers can generalize to reasoning chains longer than those encountered during training, but the computations enabling this behavior and limiting its extent remain unc…

cs.CL2026

Where Steering Signals Come From: Activation Source Selection in Activation Steering

Jiaran Ye, Lingxu Ran, Zijun Yao +5

Activation steering controls language models by adding vectors or features to hidden states at inference time, but the upstream source of these steering signals is often treated as…

cs.SE2026

ASA: Backbone-Training-Free Representation Engineering for Tool-Calling Agents

Youjin Wang, Run Zhou, Yingjie Ma +6

Adapting LLM agents to domain-specific tool calling remains notably brittle under evolving interfaces. Prompt and schema engineering is easy to deploy but often fragile under distr…

cs.AI2026

Do Latent-CoT Models Think Step-by-Step? A Mechanistic Study on Sequential Reasoning Tasks

Jia Liang, Liangming Pan

Latent Chain-of-Thought aims to enable step-by-step computation without emitting long rationales, yet its internal mechanisms remain unclear. We study CODI, a continuous-thought te…

cs.CL2025

ConciseRL: Conciseness-Guided Reinforcement Learning for Efficient Reasoning Models

Razvan-Gabriel Dumitru, Darius Peteleaza, Vikas Yadav +1

Large language models excel at complex tasks by breaking down problems into structured reasoning steps. However, reasoning traces often extend beyond reaching a correct answer, cau…

cs.LG2025

How do Transformers Learn Implicit Reasoning?

Jiaran Ye, Zijun Yao, Zhidian Huang +8

Recent work suggests that large language models (LLMs) can perform multi-hop reasoning implicitly -- producing correct answers without explicitly verbalizing intermediate steps --…

cs.CL2024

SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation

Zijun Yao, Weijian Qi, Liangming Pan +5

This paper introduces Self-aware Knowledge Retrieval (SeaKR), a novel adaptive RAG model that extracts self-aware uncertainty of LLMs from their internal states. SeaKR activates re…