The paper presents an approach to training multi-vector embedding models with consideration for the token pool.
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The authors combine LLM forecasts with external signals using weights estimated from resolved outcomes. Models help on some sets, while the system largely defers to the external forecast on a market subset.
59 days agoDaily PapersThe paper formulates intervention timing as single-token classification and generates extra supervision with a video agent. The authors compare visually grounded supervision with training from textual narration.
63 days agoDaily PapersThe authors distill visual perception from a larger agent system into a compact model for egocentric video questions. They prune the multilingual embedding table to meet the parameter limit.
63 days agoDaily PapersTRACE ranks visual tokens by relevance, diversity and screen coverage without additional model training. It also contracts the state retained from older frames.
64 days ago