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20242026
most citedAI-Driven Day-to-Day Route Choice

22 citations · 23 across the 19 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

Yongchang Peng, Qingshui Gu, Liya Zhu +31

Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally make in practice. Real-world…

cs.AI2026

GUI-GENESIS: Automated Synthesis of Efficient Environments with Verifiable Rewards for GUI Agent Post-Training

Yuan Cao, Dezhi Ran, Mengzhou Wu +9

Post-training GUI agents in interactive environments is critical for developing generalization and long-horizon planning capabilities. However, training on real-world applications…

cs.AI2026

OpAgent: Operator Agent for Web Navigation

Yuyu Guo, Wenjie Yang, Siyuan Yang +12

To fulfill user instructions, autonomous web agents must contend with the inherent complexity and volatile nature of real-world websites. Conventional paradigms predominantly rely…

cs.AI2026

AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent

Yinyi Luo, Yiqiao Jin, Weichen Yu +6

While large language model (LLM) multi-agent systems achieve superior reasoning performance through iterative debate, practical deployment is limited by their high computational co…

cs.AI2026

LongCat-Flash-Thinking-2601 Technical Report

Meituan LongCat Team, Anchun Gui, Bei Li +162

We introduce LongCat-Flash-Thinking-2601, a 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model with superior agentic reasoning capability. LongCat-Flash-Thi…