arXiv:2609.20139v1 Announce Type: cross Abstract: Vision-language models (VLMs) are fragile under image corruption. We find that the wording of the…
arXiv:2609.18462v2 Announce Type: replace-cross Abstract: FastWAM-style world action models enable efficient action-only inference, but generalize poorly under visual distribution shifts.…
arXiv:2609.19137v2 Announce Type: replace-cross Abstract: Video generation models have advanced rapidly and can now synthesize plausible videos of robot manipulation…
arXiv:2609.20130v1 Announce Type: cross Abstract: Recent memory-augmented repository-level program repair methods reuse historical repair experiences to improve LLM-based issue resolution.…
arXiv:2609.19170v1 Announce Type: new Abstract: Emphatic temporal-difference learning (ETD) stabilizes the expected off-policy TD update and changes its projection geometry,…
arXiv:2609.17631v1 Announce Type: new Abstract: AI-assisted claims can appear authoritative when evidence, analysis, human authorization, presentation, and correction history refer…
arXiv:2609.18384v1 Announce Type: cross Abstract: We present a robust benchmark for measuring cultural value orientation in large language models on…
arXiv:2609.17327v2 Announce Type: replace-cross Abstract: This paper describes our submission to the SHROOM-Visions shared task on detecting and classifying hallucinated…
arXiv:2609.18396v1 Announce Type: cross Abstract: Virtual sensing, the estimation of hard-to-measure quantities from available sensor measurements, is a critical enabler…
arXiv:2609.17171v2 Announce Type: replace-cross Abstract: The interpretability of complex machine learning models is of paramount importance, especially in real-world high-stakes…
