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20232026
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cs.CL2026

Red-TTT: Test-Time Training for Automated Jailbreaking Large Language Models

Tongyan Hu, Hao Li, Xiaogeng Liu +8

Large language models remain vulnerable to jailbreaks, and automated red teaming is the standard way to find jailbreaks in large language models at scale. Current methods either dr…

cs.CL2026

Code as Agent Harness

Xuying Ning, Katherine Tieu, Dongqi Fu +39

Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to repository-level software engineerin…

cs.CL2026

AgentSPEX: An Agent SPecification and EXecution Language

Pengcheng Wang, Jerry Huang, Jiarui Yao +7

Language-model agent systems commonly rely on reactive prompting, in which a single instruction guides the model through an open-ended sequence of reasoning and tool-use steps, lea…

cs.CL2025

FANS -- Formal Answer Selection for Natural Language Math Reasoning Using Lean4

Jiarui Yao, Ruida Wang, Tong Zhang

Large Language Models (LLMs) have displayed astonishing abilities in various tasks, especially in text generation, classification, question answering, etc. However, the reasoning a…

cs.CL2025

MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving

Ruida Wang, Rui Pan, Yuxin Li +6

Solving mathematical problems using computer-verifiable languages like Lean has significantly impacted the mathematical and computer science communities. State-of-the-art methods u…

cs.CL2023

Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Ruida Wang, Wangchunshu Zhou, Mrinmaya Sachan

*Data Synthesis* is a promising way to train a small model with very little labeled data. One approach for data synthesis is to leverage the rich knowledge from large language mode…