activity
20232026
most citedQADYNAMICS: Training Dynamics-Driven Synthetic QA Diagnostic for Zero-Shot Commonsense Question Answering

1 citations · 5 across the 24 of their papers we have counts for

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13 papers · 1 filter

cs.CR2026

Jev-Guard: Fast Routing and Auditing Agent Actions over Editable Policy Trees

Wenbin Hu, Huihao Jing, Haochen Shi +9

Agent harnesses require a low-latency guardrail model together with customizable audit policies. However, deploying an auto-regressive guardrail model remains challenging: such mod…

cs.AI2026

RadixFlow: Filling Execution Bubbles in Prefix-Cached Hybrid LLM Serving

Huihao Jing, Wenbin Hu, Shaojin Chen +6

Prefix reuse improves LLM inference by sharing the KV cache of common prompt prefixes. This helps only if the scheduler can execute a matched branch in the current worker round. Sc…

cs.AI2026

Same Operation, Different Permission: Evaluating Whether Guardrails Honor Authorization

Huihao Jing, Shaojin Chen, Wenbin Hu +5

As language-model agents write code, move money and change records on behalf of users, deciding whether an action is authorized has become a central safety problem. Guardrails are…

cs.AI2026

SkillHorizon: Constructing Long-Horizon Agent Tasks through Skill Composition

Yuxuan Liu, Zhaochen Su, Hangyu Guo +11

Long-horizon agents must complete workflows in which later activities depend on earlier outputs and changes to shared state. A key challenge for evaluation is to expand task requir…

cs.LG2026

SoFT: Soft Targets for Generalizable LLM Fine-Tuning

Huihao Jing, Wenbin Hu, Shaojin Chen +7

Distillation enables student language models to acquire new capabilities from expert teachers. However, integrating knowledge from multi-teacher, multi-domain demonstrations into a…

cs.AI2026

MultivationBench: A Benchmark for Multimodal Sequential Motivation Reasoning

Kawai Chung, Chunkit Chan, Yauwai Yim +12

Multimodal Large Language Models have sparked significant interest due to their potential for social intelligence; however, their ability to perform sequential motivation reasoning…

cs.CV2026

Finding the Right Evidence: Factor-Guided Coarse-to-Fine Reasoning for Long Videos

Baixuan Xu, Yinyui Xu, Tianshi Zheng +9

While LVLMs rapidly improve, long-video question answering still remains challenging: relevant evidence is sparse, and question-relevant context often fails to provide cues that di…

cs.LG2026

RLPF: Reinforcement Learning from Performance Feedback for Code Generation

Huihao Jing, Haozhe Cui, Wenbin Hu +9

Code models are increasingly trained with execution feedback, but most training signals still stop at correctness. This leaves an important gap for systems code: two programs can p…

cs.AI2026

Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions

Huihao Jing, Wenbin Hu, Shaojin Chen +10

The capability of LLM agents to function as the ``brain'' of a system fundamentally expands the scope of analysis beyond a standalone model. Consequently, safety is no longer only…

cs.SE2026

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization

Huihao Jing, Wenbin Hu, Shaojin Chen +5

Large language models (LLMs) can often generate functionally correct code, but their ability to produce efficient implementations for performance-critical systems tasks remains lim…

cs.CL2026

OmniCompliance-100K: A Multi-Domain, Rule-Grounded, Real-World Safety Compliance Dataset

Wenbin Hu, Huihao Jing, Haochen Shi +3

Ensuring the safety and compliance of large language models (LLMs) is of paramount importance. However, existing LLM safety datasets often rely on ad-hoc taxonomies for data genera…

cs.CL2026

SurveyLens: A Discipline-Aware Benchmark for Automatic Survey Generation

Beichen Guo, Zhiyuan Wen, Jia Gu +6

Automatic Survey Generation (ASG) aims to produce comprehensive literature surveys by retrieving, organizing, and synthesizing academic papers. Despite rapid progress in specialize…

cs.CL2026

NOVA: NOise-aware Verbal Confidence CAlibration for Robust Large Language Models in RAG Systems

Jiayu Liu, Rui Wang, Qing Zong +9

Accurately assessing model confidence is essential for deploying large language models (LLMs) in mission-critical factual domains. While retrieval-augmented generation (RAG) is wid…