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Hardware-agnostic strategies for accelerating text-to-image diffusion, such as timestep distillation and feature cach...
Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triple...
Hybrid attention models improve long-context efficiency by retaining only a subset of full-attention layers and repla...
We elucidate the design space of Representation Distribution Matching (RDM), our name for the paradigm that trains a ...
Evaluating LLM agents on benchmarks like SWE-Bench and GAIA can be expensive, time-consuming, and requires complex in...
Skills are becoming a reusable operational layer for LLM agents, encoding SOPs, domain rules, tool workflows, scripts...
Search agents powered by large language models (LLMs) are increasingly used to solve complex information-seeking task...
Diffusion language models, which generate text by denoising a token canvas bidirectionally instead of emitting tokens...
Representation alignment has become an effective way to accelerate diffusion transformer training and improve generat...
Memory for a long-horizon LLM agent is a contract about what each future decision is allowed to see. The simplest con...
Autonomous agents are increasingly expected to improve executable policies through feedback, yet existing evaluations...
Recent multimodal large language models have shown great promise in clinical image reasoning, but existing post-train...