14 citations · 27 across the 18 of their papers we have counts for
Showing 2026 · cs.CLShow all
2 papers · 2 filters
cs.CL2026
Context-Aware RL for Agentic and Multimodal LLMs
Peiyang Xu, Bangzheng Li, Sijia Liu +4
Large language models (LLMs) often fail when answering requires identifying a small but decisive piece of evidence within a long or complex context, such as a single line in a tool…
cs.CL2026
DataProphet: Demystifying Supervision Data Generalization in Multimodal LLMs
Xuan Qi, Luxi He, Dan Roth +1
Conventional wisdom for selecting supervision data for multimodal large language models (MLLMs) is to prioritize datasets that appear similar to the target benchmark, such as text-…