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Learning to coordinate retrieval signals can significantly boost multi-hop reasoning accuracy in language models.
Hindsight Supervised Learning transforms agent rollouts into a rich source of supervision, achieving superior performance with only a fraction of the required demonstrations.
MultAttnAttrib achieves superior attribution accuracy while cutting inference latency to one-seventh of traditional prompting methods, revolutionizing multimodal evidence tracing in AI.
Output compression can slash inference costs by up to 3x, but input compression leads to higher costs and accuracy collapse鈥攁n unexpected trade-off for LLMs.
Finally, AI can generate hour-long videos with consistent characters and backgrounds, thanks to a new framework that nails seamless transitions between shots.
