For An Exciting Tomorrow
arXiv:2512.20352v1 Announce Type: cross Abstract: Qualitative research faces a critical reliability challenge: traditional inter-rater agreement methods require multiple human coders,…
arXiv:2512.19025v2 Announce Type: replace-cross Abstract: Machine unlearning aims to remove specific data influences from trained models, a capability essential for…
arXiv:2511.16193v3 Announce Type: replace-cross Abstract: Rollout dominates the training time in large language model (LLM) post-training, where the trained model…
arXiv:2507.12898v4 Announce Type: replace-cross Abstract: Scaling general-purpose manipulation to new robot embodiments remains challenging: each platform typically needs large, homogeneous…
arXiv:2512.06951v2 Announce Type: replace-cross Abstract: We present a vision-action policy that won 1st place in the 2025 BEHAVIOR Challenge –…
arXiv:2512.17370v2 Announce Type: replace-cross Abstract: Existing end-to-end autonomous driving methods typically rely on imitation learning (IL) but face a key…
arXiv:2512.19007v1 Announce Type: cross Abstract: This report summarizes the 6th International Verification of Neural Networks Competition (VNN-COMP 2025), held as…
arXiv:2512.19011v1 Announce Type: cross Abstract: Prompt injection and jailbreaking attacks pose persistent security challenges to large language model (LLM)-based systems.…
arXiv:2512.17678v1 Announce Type: cross Abstract: Selecting compact and informative gene subsets from single-cell transcriptomic data is essential for biomarker discovery,…