3 papers
cs.RO2026
FARM: Find Anything using Relational Spatial Memory
Siming He, Leo Huang, Adam Lilja +7
Robots operating in homes, warehouses, and other object-rich environments need memory systems that can find specific object instances on demand. Object-level memory alone is often…
cs.CL2026
Sell More, Play Less: Benchmarking LLM Realistic Selling Skill
Xuanbo Su, Wenhao Hu, Haibo Su +4
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…
cs.CL2026
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…