most citedA Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence

3 citations · 6 across the 12 of their papers we have counts for

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cs.CL2026

EGCForest: Structured Agent Memory Organization for Enterprise Group Chats

Lingxi Cui, Jinhao Ruan, Wenqing Wei +4

Enterprise group chats record project progress, decisions, task ownership, and other organizational information valuable to enterprise agents. Reliable retrieval is challenging bec…

cs.CL2026

Gödel Forest: Balancing Search Depth and Breadth for Data-Centric Recursive Self-Improvement

Ziqi Zhao, Fanqing Meng, Haocheng Lu +4

Recursive self-improvement (RSI) aims to achieve compounding gains by having models improve themselves. While most existing RSI systems optimize external agent harnesses or prompts…

cs.CL2026

The Scaling Laws of Skills in LLM Agent Systems

Charles Chen, Qiming Yu, Yuhang Gu +12

As agent systems scale, skills accumulate into large reusable libraries, yet their scaling laws remain poorly understood. Across 15 frontier LLMs, 1,141 real-world skills, and over…

cs.CL2025

The Universal Landscape of Human Reasoning

Qiguang Chen, Jinhao Liu, Libo Qin +14

Understanding how information is dynamically accumulated and transformed in human reasoning has long challenged cognitive psychology, philosophy, and artificial intelligence. Exist…

cs.CL2025

AutoPR: Let's Automate Your Academic Promotion!

Qiguang Chen, Zheng Yan, Mingda Yang +10

As the volume of peer-reviewed research surges, scholars increasingly rely on social platforms for discovery, while authors invest considerable effort in promoting their work to en…

cs.CL2025★ 3 cited

AI4Research: A Survey of Artificial Intelligence for Scientific Research

Qiguang Chen, Mingda Yang, Libo Qin +13

Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs) such as OpenAI-o1 and DeepSeek-R1, have demonstrated remarkable capabilities in co…

cs.CL2025

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought

Tencent Hunyuan Team, Ao Liu, Botong Zhou +248

As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…