SWE-Pruner Pro: The Coder LLM Already Knows What to Prune
Pruning long context for coding agents has been a vital technology for efficient context management. While existing c...
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Pruning long context for coding agents has been a vital technology for efficient context management. While existing c...
Real-time multimodal applications, including voice agents and interactive video generation, compose heterogeneous mod...
Building assistants that can continually watch the world, remember what they see, and reason over their accumulated e...
Human-object centric video personalization (HOCVP) is a core task within subject-driven video generation. However, ex...
Large language model (LLM) post-training is essential for improving reasoning, adaptation, and alignment. Existing me...
We propose Token-Level Off-Policy Labeling (TOPL), an off-policy training paradigm that reframes post-training as a t...
This paper introduces EvolvingWorld, a framework and benchmark for character and world co-evolution in interactive li...
Video multimodal large language models (MLLMs) can describe what happens in a video, but rarely identify when the sup...
Modern video generation models are increasingly hailed as emerging world models with an internalized grasp of physica...
In line with the prevailing direction of vision research, we explore the integration of both generation and editing c...
Self-hosted AI agents read and write their own memory and configuration files to function. An agent may get compromis...
Hand-Object Interaction (HOI) synthesis is a cornerstone for animation production and embodied AI. Despite the strong...