10 citations · 24 across the 20 of their papers we have counts for
4 papers · 1 filter
Introspective Diffusion Language Models
Yifan Yu, Yuqing Jian, Junxiong Wang +12
Diffusion language models promise parallel generation, yet still lag behind autoregressive (AR) models in quality. We stem this gap to a failure of introspective consistency: AR mo…
Data Diversification Methods In Alignment Enhance Math Performance In LLMs
Berkan Dokmeci, Qingyang Wu, Ben Athiwaratkun +3
While recent advances in preference learning have enhanced alignment in human feedback, mathematical reasoning remains a persistent challenge. We investigate how data diversificati…
Rethinking Inference-Time Scaling: Efficiency Limits and Linguistic Signals
Junlin Wang, Shang Zhu, Jon Saad-Falcon +7
There is intense interest in investigating how inference time compute (ITC) (e.g. repeated sampling, refinements, etc) can improve large language model (LLM) capabilities. While br…
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang +89
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scient…