collaborators

8 papers

cs.CL2026

Efficient Reasoning Exploration via State-Conditioned Latent Steering with Progress Guidance

Hengyuan Zhang, Chenming Shang, Zunhai Su +10

Best-of- is a widely used inference strategy for complex reasoning, whose effectiveness depends on whether sampled candidates can cover diverse and high-quality reasoning paths.…

cs.LG2026

MetaRSI / RSI2: A Meta-Recursive Self-Improving System for Recursive Self-Improving Systems Themselves

Zihan Tan, Leixin Sun, Zitong Shi +28

Recursive self-improvement (RSI) lets a system improve the model-building machinery from its own failures, so every later model inherits the gain. Yet RSI has been validated almost…

cs.CL2026

EvalMem: An Operation-Level Diagnostic Framework for Long-Term Memory Systems

Zeyu Liu, Jian Zhong, Rongduo Han +12

Long-horizon interactions with LLM-based assistants require memory systems that preserve and update user states, preferences, and interaction histories. Existing evaluations report…

cs.CL2026

From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier

Eric Jiang, Xiao Liang, Yikai Zhang +19

Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in formal proof generation for we…

cs.LG2026

Beyond Outliers: A Data-Free Layer-wise Mixed-Precision Quantization Approach Driven by Numerical and Structural Dual-Sensitivity

Hengyuan Zhang, Xinrong Chen, Zunhai Su +10

Layer-wise mixed-precision quantization (LMPQ) enables effective compression under extreme low-bit settings by allocating higher precision to sensitive layers. However, existing me…

cs.LG2025

Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation

Hengyuan Zhang, Shiping Yang, Xiao Liang +8

Training student models on synthetic data generated by strong teacher models is a promising way to distilling the capabilities of teachers. However, recent studies show that strong…

cs.CL2025

GuiLoMo: Allocating Expert Number and Rank for LoRA-MoE via Bilevel Optimization with GuidedSelection Vectors

Hengyuan Zhang, Xinrong Chen, Yingmin Qiu +7

Parameter-efficient fine-tuning (PEFT) methods, particularly Low-Rank Adaptation (LoRA), offer an efficient way to adapt large language models with reduced computational costs. How…

cs.CL2025

Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective

Yiyao Yu, Yuxiang Zhang, Dongdong Zhang +9

Large Language Models (LLMs) have made notable progress in mathematical reasoning, yet often rely on single-paradigm reasoning, limiting their effectiveness across diverse tasks. W…