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13 papers · 1 filter

cs.CL2026

Jev-ToM: Evaluating Theory of Mind in Typed Decision Models

Kawai Chung, Chunkit Chan, Yuxuan Liu +9

Dialogue and collaborative assistants repeatedly judge what a partner knows, believes, or intends. Typed decision models offer a potential alternative to generative large language…

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

SkillScriptBench: Benchmarking Self-Evolution of Executable Agent Skill Packages Beyond Markdown

Yuxuan Liu, Haoran Li, Yuhao Zhang +10

Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing errors without breaking correct b…

cs.LG2026

CorrGRPO: Correlation-Normalized GRPO for Multi-Reward Learning

Wenbin Hu, Huihao Jing, Haochen Shi +3

Group Relative Policy Optimization (GRPO) is widely used to train reasoning language models, where it computes advantages by centering and normalizing rewards across rollouts of th…

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

AuthorityLens: Rethinking LLM-Based Agent Systems Through the Lens of Authority

Shaojin Chen, Huihao Jing, Wun Yu Chan +7

LLM-based agents are increasingly deployed with authority over consequential resources and decisions in real systems. These agents often operate alongside human and LLM-based parti…

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.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

ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance

Haoran Li, Yulin Chen, Huihao Jing +6

Individuals' concerns about data privacy and AI safety are highly contextualized and extend beyond sensitive patterns. Addressing these issues requires reasoning about the context…

cs.HC2026

GrandGuard: Taxonomy, Benchmark, and Safeguards for Elderly-Chatbot Interaction Safety

Changxuan Fan, Xi Yang, Yueyuan Zheng +9

As older adults increasingly use LLM-based chatbots for companionship and assistance, a safety gap is emerging. Older adults may face vulnerabilities from social isolation, limited…