most citedToken Statistics Transformer: Linear-Time Attention via Variational Rate Reduction

7 citations · 8 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.AI2025

Web World Models

Jichen Feng, Yifan Zhang, Chenggong Zhang +3

Language agents increasingly require persistent worlds in which they can act, remember, and learn. Existing approaches sit at two extremes: conventional web frameworks provide reli…

cs.AI2025

OrchDAG: Complex Tool Orchestration in Multi-Turn Interactions with Plan DAGs

Yifu Lu, Shengjie Liu, Li Dong

Agentic tool use has gained traction with the rise of agentic tool calling, yet most existing work overlooks the complexity of multi-turn tool interactions. We introduce OrchDAG, a…

cs.AI20251 cited

On Path to Multimodal Historical Reasoning: HistBench and HistAgent

Jiahao Qiu, Fulian Xiao, Yimin Wang +96

Recent advances in large language models (LLMs) have led to remarkable progress across domains, yet their capabilities in the humanities, particularly history, remain underexplored…

cs.AI2025

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes

Jiahao Qiu, Xinzhe Juan, Yimin Wang +11

While knowledge distillation has become a mature field for compressing large language models (LLMs) into smaller ones by aligning their outputs or internal representations, the dis…

cs.AI2025

Does Thinking More always Help? Mirage of Test-Time Scaling in Reasoning Models

Soumya Suvra Ghosal, Souradip Chakraborty, Avinash Reddy +6

Recent trends in test-time scaling for reasoning models (e.g., OpenAI o1, DeepSeek R1) have led to a popular belief that extending thinking traces using prompts like "Wait" or "Let…

cs.AI2025

Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution

Jiahao Qiu, Xuan Qi, Tongcheng Zhang +15

Recent advances in large language models (LLMs) have enabled agents to autonomously perform complex, open-ended tasks. However, many existing frameworks depend heavily on manually…