…need to execute, then synthesize realistic tasks around them. The result: models that look strong on existing benchmarks face a much tougher and broader test. This is an automated message from the…
…AI-generated summary Automatic generation of executable Blender code from natural language remains challenging, with state-of-the-art LLMs producing frequent syntactic errors and geometrically inconsistent objects. We present BlenderRAG, a…
…https://arxivlens.com/PaperView/Details/the-scaling-properties-of-implicit-deductive-reasoning-in-transformers-274-3e1290bd Covers the executive summary, detailed methodology, and practical applications. This is an automated message from the…
…Agents may read this hidden instruction, store it, and execute it later. In this multi-step trojan attack paradigm, no individual step appears malicious on its own, but these steps can collectively…
…irrelevant or weakly textual information can interfere with action prediction, while autoregressive text decoding adds too much latency for real-time closed-loop execution. We present VISUALTHINK-VLA, a visual intermediate-reasoning…
…Across AliasBench , SimplerEnv, LIBERO, and RoboCasa, IntentVLA improves rollout stability and outperforms strong VLA baselines View arXiv page View PDF GitHub 9 Add to collection Community This is an automated message from…
…During execution, FluxMem repairs missing links, prunes interference, aligns abstraction granularity, and distills recurrent successful trajectories into reusable procedural circuits , guided by one metric for memory generalizability and evolutionary maturity . Across three…
…They supply unambiguous detailed instructions and solely reward execution correctness, so an agent that makes a lucky guess for a missing requirement will score identically to one that would have asked to…
…https://huggingface.co/datasets/nbharaths/tau-rec This is an automated message from the Librarian Bot . I found the following papers similar to this paper. The following papers were recommended by the…
…Product T-norm relaxation makes rule execution differentiable, allowing end-to-end training on prediction accuracy alone. We evaluate NRI on rule recovery, robustness to label noise and spurious correlations, and zero…