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20232026
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cs.CL2026

NARRA-Gym for Evaluating Interactive Narrative Agents

Yue Huang, Yuchen Ma, Jiayi Ye +14

Interactive narrative tasks require LLMs to sustain a coherent, evolving story while adapting to a user over multiple turns. However, suitable benchmarks for this setting are limit…

cs.CL2025

PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory

Bowen Jiang, Yuan Yuan, Maohao Shen +13

Personalization is one of the next milestones in advancing AI capability and alignment. We introduce PersonaMem-v2, the state-of-the-art dataset for LLM personalization that simula…

cs.CL2025

Steering Multimodal Large Language Models Decoding for Context-Aware Safety

Zheyuan Liu, Zhangchen Xu, Guangyao Dou +4

Multimodal Large Language Models (MLLMs) are increasingly deployed in real-world applications, yet their ability to make context-aware safety decisions remains limited. Existing me…

cs.CL2024

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Zhangchen Xu, Fengqing Jiang, Luyao Niu +4

High-quality instruction data is critical for aligning large language models (LLMs). Although some models, such as Llama-3-Instruct, have open weights, their alignment data remain…

cs.CL2024

ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs

Fengqing Jiang, Zhangchen Xu, Luyao Niu +4

Safety is critical to the usage of large language models (LLMs). Multiple techniques such as data filtering and supervised fine-tuning have been developed to strengthen LLM safety.…