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Pulse · coingabbar.com

coingabbar.com · Oct 31

Pi Network News 2026: Four Developer Tools Launch Ahead of Summit

Pi Network News targets four new technical developer tools launched before the November 2026 summit. See what changed and why it counts.

Pulse · msn.com

msn.com · Oct 31

Elizabeth Warren slams Trump's voluntary AI safety deal with tech CEOs, says Republicans aren't doing enough to regulate AI: 'Not lifting a finger'

Sen. Elizabeth Warren (D-Mass.) has renewed her criticism of the Donald Trump administration's approach to artificial intelligence (AI) regulation, arguing that voluntary safety commitments from major tech companies are no substitute for enforceable government oversight.

Pulse · moneycontrol.com

moneycontrol.com · Oct 31

Cybersecurity gets an AI reality check as PHP, LiteLLM and eMudhra expose security gaps

Click here to track and Analyse your mutual fund investments, Stock Portfolios, Asset Allocation. Start tracking your investments in stocks, mutual fund, gold, bank deposits, property and get all your details about your investments in a single place with Moneycontrol�s Portfolio Manager.

Pulse · datacenters.economictimes.indiatimes.com

datacenters.economictimes.indiatimes.com · Oct 31

DSCI releases India-specific agentic AI liability guide

The Data Security Council of India (DSCI) has published an India-focused guide on artificial intelligence (AI) liability for agentic AI systems. This guide clarifies how responsibility is allocated across the AI value chain if an agent operates autonomously or deviates from its tasks.

Pulse

Top picks this weekarXiv

arXiv

Oct 29

Elucidating the Design Space of LM Data Attribution

Data attribution methods for Language Models (LMs) are typically evaluated using downstream tasks like fact retrieval. However, existing evaluations vary multiple dataset properties simultaneously, making it impossible to isolate exactly why an attribution algorithm fails. To diagnose these failures, we explore the design space of LLM data attribution, with a primary focus on evaluation. We introduce the Controlled Attribution Benchmark (CATT) for fact tracing, in which we fine-tune LLMs on entirely fictitious knowledge, providing unambiguous ground truth for attribution. This synthetic setup allows us to systematically alter one dataset configuration at a time, such as document redundancy and lexical distractors. With this configurable evaluation, we demonstrate that redundancy and distractors consistently degrade attribution performance. Rather than proposing a new estimator, we examine two design choices that are underexplored: the loss used to compute gradients and how per-token attribution scores are aggregated into a document score. We find that the true causal evidence within a training document is highly localized, but standard methods dilute this evidence into noise by…

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arXiv

Sep 19

MATE: Policy-Aware Security Auditing for Mobile Agents via Synthesis-Driven Trajectory Learning

Mobile agents powered by foundation models now automate complex, multi-step workflows on real devices, but their trajectories can violate app-specific security policies. Existing trajectory-level defenses rely on LLM prompting or rigid rules, and thus fail to support…

arXiv

Sep 19

From Code to Requirements: Agentic Reverse Engineering of Business Rules at Enterprise Scale

Business requirements for enterprise software systems are rarely captured in structured form; the logic resides instead in source code, configuration files, and institutional memory. When these systems must be migrated, extended, or audited, the absence of formal requirements…

arXiv

Sep 19

Learning Stiffness Dependent Fluid Structure Dynamics from Coarse Flow Representations

This paper develops a data-driven framework for long-term prediction of fluid--structure interaction (FSI) dynamics, focusing on the flow-induced vibration (FIV) of a flexible plate. A stiffness-conditioned neural evolution operator jointly represents the Eulerian flow field…

arXiv

Sep 19

ZIL: Zero-shot Image-to-LiDAR Registration

Image-to-LiDAR registration estimates the camera pose of an image with respect to a LiDAR point cloud. It has diverse applications in autonomous driving, robot navigation etc. However, state-of-the-art (SOTA) methods still 1) mostly assume same-frame inputs, struggling with the…

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