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AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning

Intermediate

Yutong Wang, Siyuan Xiong et al.Feb 26arXiv

Multi-agent systems are like teams of smart helpers, but one bad message can mislead the whole team.

#multi-agent systems#error propagation#test-time rectification

ArXiv-to-Model: A Practical Study of Scientific LM Training

Intermediate

Anuj GuptaFeb 19arXiv

This paper shows, step by step, how to train a 1.36-billion-parameter science-focused language model directly from raw arXiv LaTeX files using only 2 A100 GPUs.

#scientific language model#arXiv LaTeX#tokenization

WorldVQA: Measuring Atomic World Knowledge in Multimodal Large Language Models

Intermediate

Runjie Zhou, Youbo Shao et al.Jan 28arXiv

WorldVQA is a new test that checks if multimodal AI models can correctly name what they see in pictures without doing extra reasoning.

#WorldVQA#atomic visual knowledge#multimodal large language models

Papers3

AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning

ArXiv-to-Model: A Practical Study of Scientific LM Training

WorldVQA: Measuring Atomic World Knowledge in Multimodal Large Language Models