arXiv:2601.03378v1 Announce Type: new Abstract: Repository-level code completion benefits from retrieval-augmented generation (RAG). However, controlling cross-file evidence is difficult because chunk utility is often interaction-dependent: some snippets help only when paired with complementary context, while others harm decoding when they conflict. We propose RepoShapley, a coalition-aware context filtering framework supervised by Shapley-style marginal contributions. Our module ChunkShapley constructs offline labels by (i) single-chunk probing with teacher-forced likelihood to estimate signed, weighted effects, (ii) a surrogate game that captures […]

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arXiv:2601.00116v1 Announce Type: new Abstract: We present GRL-SNAM, a geometric reinforcement learning framework for Simultaneous Navigation and Mapping(SNAM) in unknown environments. A SNAM problem is challenging as it needs to design hierarchical or joint policies of multiple agents that control the movement of a real-life robot towards the goal in mapless environment, i.e. an environment where the map of the environment is not available apriori, and needs to be acquired through sensors. The sensors are invoked from the […]

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This paper argues that transformers are being overused as universal execution engines. I propose a meaning-first execution framework that decouples semantic proposal from model execution, allowing inference to be conditionally invoked only when needed. The result is that a large fraction of transformer calls can be skipped without changing correctness on invoked cases, suggesting many current efficiency limits are architectural rather than model-intrinsic. The work is model-agnostic and sits above existing transformers. Feedback welcome, especially around routing guarantees […]

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arXiv:2601.04298v1 Announce Type: new Abstract: Digitized, networked healthcare promises earlier detection, precision therapeutics, and continuous care; yet, it also expands the surface for privacy loss and compliance risk. We argue for a shift from siloed, application-specific protections to privacy-by-design at scale, centered on decision-theoretic differential privacy (DP) across the full healthcare data lifecycle; network-aware privacy accounting for interdependence in people, sensors, and organizations; and compliance-as-code tooling that lets health systems share evidence while demonstrating regulatory due care. We […]

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arXiv:2601.04266v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are widely deployed in safety-critical embodied AI applications such as robotics. However, their complex multimodal interactions also expose new security vulnerabilities. In this paper, we investigate a backdoor threat in VLA models, where malicious inputs cause targeted misbehavior while preserving performance on clean data. Existing backdoor methods predominantly rely on inserting visible triggers into visual modality, which suffer from poor robustness and low insusceptibility in real-world settings due to environmental […]

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arXiv:2601.02367v1 Announce Type: new Abstract: The Israeli-Palestinian conflict remains one of the most polarizing geopolitical issues, with the October 2023 escalation intensifying online debate. Social media platforms, particularly Telegram, have become central to real-time news sharing, advocacy, and propaganda. In this study, we analyze Telegram, Twitter/X, and Reddit to examine how conflict narratives are produced, amplified, and contested across different digital spheres. Building on our previous work on Telegram discourse during the 2023 escalation, we extend the analysis […]

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In the recent post, I got a lot of negative feedback for defending importance of Jesus being with you in Science (in the comment section). Do I feel wounded by that, not too much. What happened is different. From the early age I wanted that there is no secrets in the world, I believed whatever I felt had to be transmitted to the society. Why is that, because I believed when we hide something, it gives place to […]

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I think I am at least somewhat more productive than average, and people sometimes ask me for productivity tips.  So I decided to just write them all down in one place. Compound growth gets discussed as a financial concept, but it works in careers as well, and it is magic.  A small productivity gain, compounded over 50 years, is worth a lot.  So it’s worth figuring out how to optimize productivity. If you get 10% more done and […]

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Shapley values are the most widely used point-valued solution concept for cooperative games and have recently garnered attention for their applicability in explainable machine learning. Due to the complexity of Shapley value computation, users mostly resort to Monte Carlo approximations for large problems. We take a detailed look at an approximation method grounded in multilinear extensions proposed by Okhrati and Lipani (2021) under the name Owen sampling. We point out why Owen sampling is biased and propose unbiased […]

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