4 citations · 12 across the 7 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
cs.CL2025
Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation
Song Wang, Zihan Chen, Peng Wang +5
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources to address their limitations in accessing up-to-date or special…
cs.CV2025
HoneyBee: Data Recipes for Vision-Language Reasoners
Hritik Bansal, Devendra Singh Sachan, Kai-Wei Chang +4
Recent advances in vision-language models (VLMs) have made them highly effective at reasoning tasks. However, the principles underlying the construction of performant VL reasoning…