From the 1 of 21 linked papers with an AI index.
11 papers · 1 filter
MedVerse: Efficient and Reliable Medical Reasoning via DAG-Structured Parallel Execution
Jianwen Chen, Xinyu Yang, Peng Xia +7
Large language models (LLMs) have demonstrated strong performance and rapid progress in a wide range of medical reasoning tasks. However, their sequential autoregressive decoding f…
MetaClaw: Just Talk -- An Agent That Meta-Learns and Evolves in the Wild
Peng Xia, Jianwen Chen, Xinyu Yang +10
Large language model (LLM) agents are increasingly used for complex tasks, yet deployed agents often remain static, failing to adapt as user needs evolve. This creates a tension be…
Reliable and Responsible Foundation Models: A Comprehensive Survey
Xinyu Yang, Junlin Han, Rishi Bommasani +49
Foundation models, including Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Image Generative Models (i.e, Text-to-Image Models and Image-Editing Models), a…
ThetaEvolve: Test-time Learning on Open Problems
Yiping Wang, Shao-Rong Su, Zhiyuan Zeng +13
Recent advances in large language models (LLMs) have enabled breakthroughs in mathematical discovery, exemplified by AlphaEvolve, a closed-source system that evolves programs to im…
Efficient Parallel Samplers for Recurrent-Depth Models and Their Connection to Diffusion Language Models
Jonas Geiping, Xinyu Yang, Guinan Su
Language models with recurrent depth, also referred to as universal or looped when considering transformers, are defined by the capacity to increase their computation through the r…
Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation
Xinyu Yang, Yuwei An, Hongyi Liu +2
Autoregressive Large Language Models (AR-LLMs) frequently exhibit implicit parallelism in sequential generation. Inspired by this, we introduce Multiverse, a new generative model t…