…AI-generated summary The landscape of high-performance image generation models is currently shifting from the inefficient multi-step ones to the efficient few-step counterparts (e.g, Z-Image-Turbo and…
…from temporal blindness in dynamic environments, but a training-free correction method using quadratic optimization improves performance by addressing pace and path dynamics simultaneously. AI-generated summary Vision-Language-Action (VLA) models…
…Rather than relying on an LLM to directly produce a final scene, Function2Scene performs iterative evaluation and refinement through a tool-augmented check-and-repair loop , combining geometric measurements , LLM-based contextual…
…However, despite their strong performance in static scene perception, these models remain limited in responding to dynamic human instructions, which restricts their use in interactive applications. Existing editing methods typically rely on…
…AI-generated summary Following the recent achievement of gold-medal performance on the IMO by frontier LLMs, the community is searching for the next meaningful and challenging target for measuring LLM reasoning…
…At inference time, UniSteer performs flow inversion by partially transporting a source activation toward a latent state and regenerating it under a target textual condition before injecting it back into the frozen…
…Entropy-Progress Aligned Group Relative Policy Optimization with Implicit Process Guidance (2026) ResRL: Boosting LLM Reasoning via Negative Sample Projection Residual Reinforcement Learning (2026) T$^2$PO: Uncertainty-Guided Exploration Control for…
…Many existing efficiency methods improve throughput by changing the rollout or optimization regime, for example, through off-policy execution, replay, or lower-precision generation. We study speculative decoding as a lossless acceleration…
…We then propose Forcing-KV, a hybrid KV cache compression strategy that performs structured static pruning for static heads and dynamic pruning based on segment-wise similarity for dynamic heads . While maintaining…
…Using Direct Preference Optimization , we encourage models to prefer attribute-affordance reasoning grounded in visual evidence over hallucinated alternatives. In addition, we incorporate supervision derived from an affordance knowledge base to guide…