3 citations · 5 across the 14 of their papers we have counts for
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cs.AI2026
TRACER: Per-Tool Context Retention for LLM Agents via Consequence-Attributed Reinforcement Learning
Ziqi Lin, Ye Wu, Mengying Yang +4
Enterprise data agents answer business queries by chaining many tool calls over multiple reasoning steps, routinely accumulating hundreds of thousands of context tokens per session…
cs.AI2026
KnowU-Bench: Towards Interactive, Proactive, and Personalized Mobile Agent Evaluation
Tongbo Chen, Zhengxi Lu, Zhan Xu +13
Personalized mobile agents that infer user preferences and calibrate proactive assistance hold great promise as everyday digital assistants, yet existing benchmarks fail to capture…
cs.AI2026
Search, Do not Guess: Teaching Small Language Models to Be Effective Search Agents
Yizhou Liu, Qi Sun, Yulin Chen +2
Agents equipped with search tools have emerged as effective solutions for knowledge-intensive tasks. While Large Language Models (LLMs) exhibit strong reasoning capabilities, their…