61 citations · 118 across the 23 of their papers we have counts for
10 papers · 1 filter
Synthesizing Agentic Data for Web Agents with Progressive Difficulty Enhancement Mechanisms
Shrey Pandit, Xuan-Phi Nguyen, Yifei Ming +4
Web-based 'deep research' agents aim to solve complex question - answering tasks through long-horizon interactions with online tools. These tasks remain challenging, as the underly…
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…
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…
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…
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…
MAS-ZERO: Designing Multi-Agent Systems with Zero Supervision
Zixuan Ke, Austin Xu, Yifei Ming +4
Multi-agent systems (MAS) leveraging the impressive capabilities of Large Language Models (LLMs) hold significant potential for tackling complex tasks. However, most current MAS de…
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…
NAACL2025 Tutorial: Adaptation of Large Language Models
Zixuan Ke, Yifei Ming, Shafiq Joty
This tutorial on adaptation of LLMs is designed to address the growing demand for models that go beyond the static capabilities of generic LLMs by providing an overview of dynamic,…
Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings
Austin Xu, Srijan Bansal, Yifei Ming +2
The large language model (LLM)-as-judge paradigm has been used to meet the demand for a cheap, reliable, and fast evaluation of model outputs during AI system development and post-…
Demystifying Domain-adaptive Post-training for Financial LLMs
Zixuan Ke, Yifei Ming, Xuan-Phi Nguyen +2
Domain-adaptive post-training of large language models (LLMs) has emerged as a promising approach for specialized domains such as medicine and finance. However, significant challen…