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Pulse · rebellionresearch.com

rebellionresearch.com · Nov 1

How to Secure AI Agents: Identifying Hidden Risks in Third-Party AI Skills

Pulse · techtimes.com

techtimes.com · Nov 1

Parse and Nomic Launch Cascade: AI Immune Drug Discovery Gets Its Missing Protein Signal

AI drug discovery single-cell datasets now have their first systematic secretome training layer: Parse Biosciences and Nomic Bio launched Cascade, pairing 100 million RNA-seq profiles with matched 1,000-protein secretome reads across 150,000-plus immune perturbation conditions, backed by GSK,

Pulse · techgig.com

techgig.com · Nov 1

Spring ecosystem releases first release candidates for 17 projects

The Spring ecosystem announced the first release candidates for 17 projects, including Spring Boot 4.2.0-RC1 and Spring Framework 7.1.0-RC1. These updates deliver bug fixes, dependency upgrades, and new features across various components. Developers can expect improved performance and enhanced functionalities in these latest releases.

Pulse · msn.com

msn.com · Oct 31

Taiwan's MediaTek eyes 20% share of global AI chip market

MediaTek (TWSE: 2454) expects to capture about 20% of the global market for application-specific integrated circuits (ASICs) used in AI accelerators next year, Focus Taiwan reported on October 31. Chief Executive Officer Rick Tsai told investors the custom chip should bring in about $16bn in sales in 2027,

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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

Oct 28

HotPOT: Operator Transformer with Heterogeneous Physics Experts for Large-Scale PDE Pre-training

Large-scale PDE pre-training trains a single model on the data from multiple partial differential equations (PDEs). However, adding heterogeneous PDEs with different governing equations, physical variables, and variable interactions does not always improve predictive…

arXiv

Oct 28

Disparity Laundering: Consensus Without Fairness in Clinical Multi-Agent Systems

Clinical large language models are increasingly fielded as multi-agent teams, on the assumption that deliberation averages out individual error. It does not average out bias. Across a full factorial of five model families and four aggregation topologies on 120 real MIMIC-IV…

arXiv

Oct 28

Skeleton Coding: Program Structure as a Specification for Agents

Coding agents are typically provided end-to-end behavioral specifications that the code they produce should satisfy, such as tests and input--output examples. How many such specifications must a developer provide, and which ones, for the agent to produce the developer's…

Hacker News

Oct 28

Artificial Analysis Intelligence Index v5

Discussed on Hacker News · 95 points · 82 comments · artificialanalysis.ai

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