collaborators

9 papers

cs.CL2026

GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language Models

Zhiwen Ruan, Yichao Du, Jianjie Zheng +6

A promising paradigm for adapting instruction-tuned language models is to learn task-specific updates on a pretrained base model and subsequently merge them into the instruction-tu…

cs.CL2026

Evaluating Memory Capability in Continuous Lifelog Scenario

Jianjie Zheng, Zhichen Liu, Zhanyu Shen +6

Nowadays, wearable devices can continuously lifelog ambient conversations, creating substantial opportunities for memory systems. However, existing benchmarks primarily focus on on…

cs.AI2026

SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks

Tianyi Wang, Yixia Li, Long Li +6

Proximal Policy Optimization (PPO) is central to aligning Large Language Models (LLMs) in reasoning tasks with verifiable rewards. However, standard token-level PPO struggles in th…

cs.CL2026

InstructDiff: Domain-Adaptive Data Selection via Differential Entropy for Efficient LLM Fine-Tuning

Junyou Su, He Zhu, Xiao Luo +6

Supervised fine-tuning (SFT) is fundamental to adapting large language models, yet training on complete datasets incurs prohibitive costs with diminishing returns. Existing data se…

cs.CL2025

G2: Guided Generation for Enhanced Output Diversity in LLMs

Zhiwen Ruan, Yixia Li, Yefeng Liu +5

Large Language Models (LLMs) have demonstrated exceptional performance across diverse natural language processing tasks. However, these models exhibit a critical limitation in outp…

cs.CL2025

Beyond the Surface: Enhancing LLM-as-a-Judge Alignment with Human via Internal Representations

Peng Lai, Jianjie Zheng, Sijie Cheng +4

The growing scale of evaluation tasks has led to the widespread adoption of automated evaluation using LLMs, a paradigm known as "LLM-as-a-judge". However, improving its alignment…