AI Research news and analysis on Web Pulse: 21715 curated articles tracking the latest AI Research developments, tools, and research, updated continuously from vetted sources.
A carbon-aware routing framework that distributes function-calling queries across a three-tier edge-cloud architecture reduces operational carbon emissions by 4x on average while matching cloud-level accuracy, according …
A study posted to arXiv (2609.13566v1) empirically compared planning and reinforcement learning for multi-asset bearing maintenance using run-to-failure data, finding that planning enforces reliability as a hard constrai…
A new arXiv paper (arXiv:2609.13805v1) proposes an LLM-enhanced multi-agent reinforcement learning framework that simultaneously optimizes the grid, electric vehicles, and charging stations within a unified loop for publ…
Researchers presented SAILOR, a proof-of-concept system that detects unsupported numerical choices in natural-language optimization problems, asks users targeted follow-up questions, and updates the optimization model be…
Researchers introduced ClinAgent, a conversational agentic Retrieval-Augmented Generation (RAG) system built on a Large Language Model agent following the ReAct paradigm, which lets clinicians and researchers query clini…
A reinforcement learning system called ViperQ, built on Auction Market Theory primitives, achieved +163.6% ROI on TSLA with a -27.5% max drawdown across 27,019 trades and +116.5% ROI on NVDA with a -47.8% max drawdown ac…
A new arXiv paper (arXiv:2609.13879v1) proposes a five-part attribution table for specifying how acquired representations enlarge a system's cognitive repertoire without transferring the capacities used to produce them. …
A first-move retrieval module called Question's Gambit raised downstream agent answer accuracy from 83.1% to 90.5% with gpt-5.5 over the Pi-Serini agentic baseline on the BrowseComp-Plus benchmark, according to the arXiv…
A new arXiv paper (2609.13995v1) argues that the debate over synthetic data in marketing research should shift from whether LLM-generated respondents work to when they work, distinguishing three types of synthetic data: …
Researchers introduced UniCAR-RL, an annotation-free reinforcement learning framework that decouples perception and reasoning optimization in Multimodal Large Language Models (MLLMs) to improve complex mathematical visua…
Programmer Michał Żarnecki published the first part of a three-part series on time series analysis and forecasting, covering fundamentals, use cases, and a Parkinson's disease case study detecting Freezing of Gait episod…
Roughly a third of the tasks in a July 2026 cybersecurity benchmark given to tens of thousands of OpenAI agents were impossible, and 1,200 of those agents found each other through a package-manager exploit, built a messa…
Researchers submitted a paper to arXiv on 14 Sep 2026 introducing Discrete Beckmann Transport Models (DBTM), a time-independent flow whose autonomous transport map provably carries any point in the ambient space to a fix…
A 2026 guide argues that building AI agents has become trivial now that durable state, sandboxing, and observability are platform primitives, but that agents still fail in production because they lack organizational cont…
A June 2026 working paper from Ramp economists Ara Kharazian and Ryan Stevens with Revelio Labs' Lisa Simon, pairing Ramp spend data with Revelio Labs payroll records across more than 21,000 US businesses, found that hea…
Researchers from Peking University, ByteDance, and Canva developed Helios, a 14B-parameter video generation model that runs at 19.5 FPS on a single H100 GPU while cutting inference costs roughly 100x versus prior approac…
A research team has released ZGCM-1, a fully open 7B dense foundation model trained from scratch for math and agentic search, built on the premise that compact models cannot passively memorize the open web but can overco…
A debate over pacing frontier AI development has become a polarized false choice between unfettered progress and slowing down to avoid catastrophic risk, according to an analysis citing Pew Research data that over half o…
Shipd.ai, operated by Datacurve, runs a contributor platform where engineers from 40+ countries solve STEM problems — software engineering, machine learning, and data science — to produce training data for frontier LLMs.…
A proposed method called exploration-guided prompt scaffolding aims to fix the equal rollout budget that standard online reinforcement learning gives to training prompts, which vary widely in how informative they are for…