5 papers
PhotoCraft: Agentic Reasoning with Hierarchical Self-Evolving Memory for Deep Image Search
Kailin Lyu, Zhiqiang Yuan, Jianwei He +9
Deep Image Search requires multi-step reasoning over rich contextual cues, such as time, location, and event relations. However, most existing LLM-based agents are stateless and re…
MemMark: State-Evolution Attribution Watermarking for Agent Long-Term Memory Systems
Haobo Zhang, Xutao Mao, Guangyuan Dong +5
Memory-backed agents need provenance that can survive leaked or migrated snapshots, where logs, visible outputs, and trusted metadata may be absent. We propose MemMark, a state-evo…
Sell More, Play Less: Benchmarking LLM Realistic Selling Skill
Xuanbo Su, Wenhao Hu, Le Zhan +8
Sales dialogues require multi-turn, goal-directed persuasion under asymmetric incentives, which makes them a challenging setting for large language models (LLMs). Yet existing dial…
Watch the Model Think: On-Policy Extraction of Activation Steering Vectors
Xuanbo Su, Hao Luo, Yingfang Zhang +4
When a model solves a problem on one attempt and fails it on the next, what separates the two is rarely the final answer token; it is the trajectory that reached it. Contrastive ac…
Mistake Notebook Learning: Batch-Clustered Failures for Training-Free Agent Adaptation
Xuanbo Su, Yingfang Zhang, Hao Luo +2
With the growing adoption of Large Language Model (LLM) agents in persistent, real-world roles, they naturally encounter continuous streams of tasks and inevitable failures. A key…