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20242026
most citedA Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems

3 citations · 4 across the 7 of their papers we have counts for

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cs.AI2026

Privileged Likelihood Is Not Automatically Value: Three Checks for Token Credit in On-Policy Self-Distillation

Xuan-Phi Nguyen, Shrey Pandit, Yiran Zhao +3

Outcome verifiers score completed reasoning traces but do not assign credit to intermediate tokens. Privileged self-distillation attempts to fill this gap by rescoring a model's ow…

cs.AI2026

MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks

Zixuan Ke, Yifei Ming, Austin Xu +7

While multi-agent systems (MAS) promise elevated intelligence through coordination of agents, current approaches to automatic MAS design under-deliver. Such shortcomings stem from…

cs.AI20263 cited

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…

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

SFR-DeepResearch: Towards Effective Reinforcement Learning for Autonomously Reasoning Single Agents

Xuan-Phi Nguyen, Shrey Pandit, Revanth Gangi Reddy +4

Equipping large language models (LLMs) with complex, interleaved reasoning and tool-use capabilities has become a key focus in agentic AI research, especially with recent advances…

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…