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From the 3 of 18 linked papers with an AI index.

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20242026
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cs.CL2026

Can Language Models Imagine Without Seeing? Ekphrasis: Measuring Visual Creative Ideation in Text-Only LLMs

Hongyu Luo, He Wang, Huihao Jing +6

Current evaluations do not isolate whether text-only language models can originate visual concepts before image generation. Fluent visual prose can hide visual-plan failures: an an…

cs.CL2026

SING: Synthetic Intention Graph for Scalable Active Tool Discovery in LLM Agents

Qiao Xiao, Haochen Shi, Yisen Gao +9

Large language model (LLM) agents increasingly rely on agent harnesses that manage context, tools, and multi-turn execution, making tools a central interface for acting in realisti…

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.CL2025

MCIP: Protecting MCP Safety via Model Contextual Integrity Protocol

Huihao Jing, Haoran Li, Wenbin Hu +5

As Model Context Protocol (MCP) introduces an easy-to-use ecosystem for users and developers, it also brings underexplored safety risks. Its decentralized architecture, which separ…

cs.CL2025

Safety Compliance: Rethinking LLM Safety Reasoning through the Lens of Compliance

Wenbin Hu, Huihao Jing, Haochen Shi +2

The proliferation of Large Language Models (LLMs) has demonstrated remarkable capabilities, elevating the critical importance of LLM safety. However, existing safety methods rely o…