activity
20242026
collaborators

9 papers

math-ph2026

Counterexamples to the total-current Hohenberg-Kohn conjecture

Andre Laestadius, Mihály A. Csirik

The total-current Hohenberg-Kohn conjecture asserts that the ground-state particle density and total current determine the scalar potential up to an additive constant and the vecto…

cs.CL2026

Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing

Yutong Yin, Mingyu Jin, Jin Pan +12

Test-time scaling improves language-model reasoning, but existing approaches often face a difficult trade-off: long chain-of-thought sampling remains single-threaded, while sentenc…

cs.AI2026

Agent MechSuits: Mechanistic Subspace Safety Steering for Multi-Turn CLI Agents

Weidi Luo, Qiming Zhang, Yihao Quan +5

Command-Line Interface (CLI) agents based on large language models (LLMs) demonstrate remarkable autonomous capabilities, but they also introduce significant safety and misuse risk…

cs.CL2026

All Circuits Lead to Rome: Rethinking Functional Anisotropy in Circuit and Sheaf Discovery for LLMs

Xi Chen, Mingyu Jin, Jingcheng Niu +7

In this paper, we present empirical and theoretical evidence against a central but largely implicit assumption in circuit and sheaf discovery (CSD), which we term the Functional An…

cs.CL2026

Farther the Shift, Sparser the Representation: Analyzing OOD Mechanisms in LLMs

Mingyu Jin, Yutong Yin, Jingcheng Niu +7

In this work, we investigate how Large Language Models (LLMs) adapt their internal representations when encountering inputs of increasing difficulty, quantified as the degree of ou…

cs.CL2025

SAGE: An Agentic Explainer Framework for Interpreting SAE Features in Language Models

Jiaojiao Han, Wujiang Xu, Mingyu Jin +1

Large language models (LLMs) have achieved remarkable progress, yet their internal mechanisms remain largely opaque, posing a significant challenge to their safe and reliable deplo…

cs.LG2025

EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning

Wujiang Xu, Wentian Zhao, Zhenting Wang +6

Training LLM agents in multi-turn environments with sparse rewards, where completing a single task requires 30+ turns of interaction within an episode, presents a fundamental chall…

cs.CL2024

Data-centric NLP Backdoor Defense from the Lens of Memorization

Zhenting Wang, Zhizhi Wang, Mingyu Jin +3

Backdoor attack is a severe threat to the trustworthiness of DNN-based language models. In this paper, we first extend the definition of memorization of language models from sample…

cs.CL2024

Exploring Multilingual Probing in Large Language Models: A Cross-Language Analysis

Daoyang Li, Haiyan Zhao, Qingcheng Zeng +1

Probing techniques for large language models (LLMs) have primarily focused on English, overlooking the vast majority of the world's languages. In this paper, we extend these probin…