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From the 1 of 30 linked papers with an AI index.

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20242026
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cs.CL2026

SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information

Junjie Ye, Zhuohui Sheng, Shaofan Liu +12

Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across multiple applications (apps)…

cs.CL2026

IACM-RL: Intent-Aware Context Management and Reinforcement Learning for Complex Tool Invocation under Dynamic Intent Fluctuations

Dingwei Zhu, Jiahan Li, Chengjun Pan +22

Executing long-horizon tool invocations in real-world environments is severely challenged by dynamic user intent noise. Existing methods attempt robustness via implicit history sca…

cs.CL2026

AI Can Learn Scientific Taste

Jingqi Tong, Mingzhe Li, Hangcheng Li +20

The paper introduces a reinforcement‑learning framework that uses citation‑based community feedback to train models that can judge the impact of scientific papers and generate high…

cs.CL2026

SciAgentGym: Benchmarking Multi-Step Scientific Tool-use in LLM Agents

Yujiong Shen, Yajie Yang, Zhiheng Xi +17

Scientific reasoning inherently demands integrating sophisticated toolkits to navigate domain-specific knowledge. Yet, current benchmarks largely overlook agents' ability to orches…

cs.CL2026

Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies

Ming Zhang, Jiabao Zhuang, Wenqing Jing +18

Deep Research Agents increasingly automate survey writing, yet existing benchmarks do not jointly test whether they retrieve the papers experts consider essential and organize thos…

cs.CL2026

CL-bench Life: Can Language Models Learn from Real-Life Context?

Shihan Dou, Yujiong Shen, Chenhao Huang +35

Today's AI assistants such as OpenClaw are designed to handle context effectively, making context learning an increasingly important capability for models. As these systems move be…