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20242026
most citedDeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

884 citations · 884 across the 8 of their papers we have counts for

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cs.CL2026

Adam's Law: Textual Frequency Law on Large Language Models

Hongyuan Adam Lu, Z. L., Victor Wei +5

While textual frequency has been validated as relevant to human cognition in reading speed, its relatedness to Large Language Models (LLMs) is seldom studied. We propose a novel re…

cs.CL2026

Real-World Doctor Agent with Proactive Consultation through Multi-Agent Reinforcement Learning

Yichun Feng, Jiawei Wang, Lu Zhou +3

Large language models (LLMs) struggle in real-world clinical consultations. Single-turn consultation systems require patients to describe all symptoms at once, which often leads to…

cs.CL2026

Gender Bias in MT for a Genderless Language: New Benchmarks for Basque

Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez

Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data…

cs.CL2026

WideSeek: Advancing Wide Research via Multi-Agent Scaling

Ziyang Huang, Haolin Ren, Xiaowei Yuan +6

Search intelligence is evolving from Deep Research to Wide Research, a paradigm essential for retrieving and synthesizing comprehensive information under complex constraints in par…

cs.CL2026884 cited

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

DeepSeek-AI, Daya Guo, Dejian Yang +195

General reasoning represents a long-standing and formidable challenge in artificial intelligence. Recent breakthroughs, exemplified by large language models (LLMs) and chain-of-tho…

cs.CL2025

Reliable Decision Support with LLMs: A Framework for Evaluating Consistency in Binary Text Classification Applications

Fadel M. Megahed, Ying-Ju Chen, L. Allision Jones-Farmer +3

This study introduces a framework for evaluating consistency in large language model (LLM) binary text classification, addressing the lack of established reliability assessment met…