most citedSFR-RAG: Towards Contextually Faithful LLMs

2 citations · 2 across the 2 of their papers we have counts for

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cs.AI2026

SkillOrchestra: Learning to Route Agents via Skill Transfer

Jiayu Wang, Yifei Ming, Zixuan Ke +3

Compound AI systems promise capabilities beyond those of individual models, yet their success depends critically on effective orchestration. Existing routing approaches face two li…

cs.AI2025

Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math

Shrey Pandit, Austin Xu, Xuan-Phi Nguyen +3

Large language model (LLM)-based reasoning systems have recently achieved gold medal-level performance in the IMO 2025 competition, writing mathematical proofs where, to receive fu…

cs.AI2025

LiveResearchBench: A Live Benchmark for User-Centric Deep Research in the Wild

Jiayu Wang, Yifei Ming, Riya Dulepet +7

Deep research -- producing comprehensive, citation-grounded reports by searching and synthesizing information from hundreds of live web sources -- marks an important frontier for a…

cs.AI2025

Helpful Agent Meets Deceptive Judge: Understanding Vulnerabilities in Agentic Workflows

Yifei Ming, Zixuan Ke, Xuan-Phi Nguyen +2

Agentic workflows -- where multiple large language model (LLM) instances interact to solve tasks -- are increasingly built on feedback mechanisms, where one model evaluates and cri…

cs.AI2025

Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning

Jiayu Wang, Yifei Ming, Zixuan Ke +4

Reinforcement learning (RL) has become the dominant paradigm for improving the performance of language models on complex reasoning tasks. Despite the substantial empirical gains de…

cs.AI2025

A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems

Zixuan Ke, Fangkai Jiao, Yifei Ming +9

Reasoning is a fundamental cognitive process that enables logical inference, problem-solving, and decision-making. With the rapid advancement of large language models (LLMs), reaso…