collaborators

7 papers

cs.CL2026

Same Question, Different Answer? Measuring and Mitigating Prompt Privilege for Equitable AI Access

Lier Jin, Lan Hu, Binqi Shen +2

Large language models (LLMs) are increasingly integrated into healthcare, education, public services, and everyday decision making. They should provide comparable assistance regard…

cs.CL2026

DriftGuard: Safety-Aware Multi-Monitor Detection and Selective Adaptation for Evolving Toxicity Moderation

Yuting Xin, Hanyu Cai, Binqi Shen +2

Automated toxicity moderation systems operate in dynamic online environments where harmful behavior evolves through coded language, shifting targets, and strategic adaptation to en…

cs.CL2026

The Efficiency Frontier: A Unified Framework for Cost-Performance Optimization in LLM Context Management

Binqi Shen, Lier Jin, Hanyu Cai +2

Large language models (LLMs) increasingly rely on long-context processing, but expanding context windows introduces substantial computational and financial costs. Existing context…

cs.CL2026

Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, and LLaMA

Hanyu Cai, Binqi Shen, Lier Jin +2

Prompt engineering has emerged as a critical factor influencing large language model (LLM) performance, yet the impact of pragmatic elements such as linguistic tone and politeness…

cs.LG2026

HISR: Hindsight Information Modulated Segmental Process Rewards For Multi-turn Agentic Reinforcement Learning

Zhicong Lu, Zichuan Lin, Wei Jia +7

While large language models excel in diverse domains, their performance on complex longhorizon agentic decision-making tasks remains limited. Most existing methods concentrate on d…

cs.CL2025

Rectify Evaluation Preference: Improving LLMs' Critique on Math Reasoning via Perplexity-aware Reinforcement Learning

Changyuan Tian, Zhicong Lu, Shuang Qian +8

To improve Multi-step Mathematical Reasoning (MsMR) of Large Language Models (LLMs), it is crucial to obtain scalable supervision from the corpus by automatically critiquing mistak…