Daniel Huynh

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upvoted a paper 5 days ago

OSWorld-MCP: Benchmarking MCP Tool Invocation In Computer-Use Agents

Paper • 2510.24563 • Published 6 days ago • 22

upvoted 2 papers about 1 month ago

Video models are zero-shot learners and reasoners

Paper • 2509.20328 • Published Sep 24 • 96

What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT

Paper • 2509.19284 • Published Sep 23 • 22

upvoted 2 papers about 2 months ago

UItron: Foundational GUI Agent with Advanced Perception and Planning

Paper • 2508.21767 • Published Aug 29 • 12

Ovis2.5 Technical Report

Paper • 2508.11737 • Published Aug 15 • 109

upvoted 3 papers 3 months ago

Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models

Paper • 2508.02120 • Published Aug 4 • 19

Attention Basin: Why Contextual Position Matters in Large Language Models

Paper • 2508.05128 • Published Aug 7 • 4

MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents

Paper • 2507.19478 • Published Jul 25 • 30

upvoted a paper 4 months ago

Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning

Paper • 2507.00432 • Published Jul 1 • 79

upvoted 6 papers 5 months ago

Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs

Paper • 2506.14245 • Published Jun 17 • 42

DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents

Paper • 2506.11763 • Published Jun 13 • 71

LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?

Paper • 2506.11928 • Published Jun 13 • 23

Hidden in plain sight: VLMs overlook their visual representations

Paper • 2506.08008 • Published Jun 9 • 7

What Makes a Good Natural Language Prompt?

Paper • 2506.06950 • Published Jun 7 • 11

Comment on The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

Paper • 2506.09250 • Published Jun 10 • 27

upvoted 5 papers 7 months ago

Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead

Paper • 2504.00294 • Published Mar 31 • 10

I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders

Paper • 2503.18878 • Published Mar 24 • 119

Think Twice: Enhancing LLM Reasoning by Scaling Multi-round Test-time Thinking

Paper • 2503.19855 • Published Mar 25 • 29

UI-R1: Enhancing Action Prediction of GUI Agents by Reinforcement Learning

Paper • 2503.21620 • Published Mar 27 • 62

Can Large Vision Language Models Read Maps Like a Human?

Paper • 2503.14607 • Published Mar 18 • 10