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Every LLM API call depends on the inference engine underneath it. Tokenization, scheduling, prefill, decode, KV cache, batching, and streami…

applicationstogether-ai--x

Every LLM API call depends on the inference engine underneath it. Tokenization, scheduling, prefill, decode, KV cache, batching, and streaming determine whether the experience is fast, scalable, and p

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Every9D-21M: Large-Scale Real-World 9D Canonicalization of Everyday Objects

DGX agent

arXiv:2605.28270v1 Announce Type: new Abstract: Estimating the 9D pose of everyday objects from a single real-world image remains challenging. This is largely due to the lack of large-scale supervisio

model-releasesarxiv-cs-cv

28 May 2026

Everyone holds up Banks as seeing the future of AI, but come on...

applicationsethan-mollick--x

Ethan Mollick critiques the widespread praise for Joseph E. Banks's predictions about AI's future, suggesting that the expectations placed on his foresight may be overstated. The post likely argues fo

Evolving and Detecting Multi-Turn Deception using Geometric Signatures

arXiv:2605.27671v1 Announce Type: cross Abstract: Safety defenses for large language models (LLMs) are typically trained and evaluated on single-turn prompts, yet real attacks often unfold as indirect

safetyarxiv-cs-lg

Evolving Dataflow to process massive datasets for machine learning

model-releasesgoogle-cloud-ai

Google created MapReduce more than 20 years ago to solve the scaling problems in data processing that the then young company was running into. The AI era that we are in now demands efficient, large-sc

EvoSpec: Evolving Speculative Decoding via Real-Time Vocabulary and Parameter AdaptationTarget

arXiv:2605.27390v1 Announce Type: cross Abstract: Speculative decoding accelerates Large Language Model inference via a draft-then-verify paradigm, yet the output projection layer becomes a bottleneck

Examining Agents' Bias Amplification versus Suppression in Multi-Agent Systems

arXiv:2605.28098v1 Announce Type: new Abstract: Multi-agent systems are increasingly deployed to support various tasks where agents interact to achieve individual and collective objectives. Although t

safetyarxiv-cs-ai

Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State

arXiv:2603.14515v2 Announce Type: replace Abstract: Neural-network wave functions in Variational Monte Carlo (VMC) have achieved great success in accurately representing both ground and excited states

Explaining Digital Pathology Models via Clustering Activations

arXiv:2511.14558v2 Announce Type: replace Abstract: We present a clustering-based explainability technique for digital pathology models based on convolutional neural networks. Unlike commonly used met

researcharxiv-cs-cv

Explaining is Harder Than Predicting Alone: Evaluating Concept-based Explanations of MLLMs as ICL Visual Classifiers

arXiv:2605.28215v1 Announce Type: new Abstract: In-context learning (ICL) enables multimodal large language models (MLLMs) to classify images from a few labelled examples. Yet, how these models use th

researcharxiv-cs-ai

Explanation Generation for Contradiction Reconciliation with LLMs

arXiv:2603.22735v2 Announce Type: replace Abstract: Existing NLP work commonly treats contradictions as errors to be resolved by choosing which statements to accept or discard. Yet a key aspect of hum

researcharxiv-cs-cl

Explicit Critic Guidance for Aligning Diffusion Models

arXiv:2605.27736v1 Announce Type: cross Abstract: Online reinforcement learning is becoming increasingly important for aligning diffusion models with non-differentiable objectives. However, existing m

researcharxiv-cs-cv

Exploratory Experience Shapes the Geometry of Predictive Representations

model-releasesarxiv-cs-lg

arXiv:2605.27929v1 Announce Type: cross Abstract: Active sensing links behavior and learning through an action-perception loop: actions determine the observations used to update internal predictive mo

Expressive Power of Floating-Point Neural Networks with Arbitrary Reduction Orders and Inexact Activation Implementations

arXiv:2605.28704v1 Announce Type: new Abstract: Most existing expressivity theories for neural networks assume exact real arithmetic, whereas practical neural networks are executed under finite-precis

Extensions of Robbins-Siegmund Theorem with Applications in Reinforcement Learning

arXiv:2509.26442v2 Announce Type: replace Abstract: The Robbins-Siegmund theorem establishes the convergence of stochastic processes that are almost supermartingales and is one of the most commonly us

Extracting Small Translation Specialists from LLMs by Aggressively Pruning Experts

arXiv:2605.28042v1 Announce Type: cross Abstract: Modern large language models (LLMs) achieve state-of-the-art machine translation performance, but they do so as broad generalists largely trained for

researcharxiv-cs-ai

Extrapolative Weight Averaging Reveals Correctness-Efficiency Frontiers in Code RL

arXiv:2605.28751v1 Announce Type: cross Abstract: Linear interpolation between fine-tuned checkpoints has been shown to trace the Pareto front between competing objectives, but whether extrapolative w

agentsarxiv-cs-ai

F Scott Fitzgerald, writing about someone who may as well have been Peter Thiel: “They were careless people, Tom and Daisy- they smashed up …

F Scott Fitzgerald, writing about someone who may as well have been Peter Thiel: “They were careless people, Tom and Daisy- they smashed up things and creatures and then retreated back into their mone

safetygary-marcus--x

FABSVer: Faster Training and Better Self-Verification for LLM Mathematical Reasoning

arXiv:2605.28389v1 Announce Type: new Abstract: While large language models have made significant progress in mathematical reasoning, they remain unreliable at judging the correctness of their own sol

safetyarxiv-cs-cl

FactReview: Evidence-Grounded Peer Review with Execution-Based Claim Verification

arXiv:2604.04074v3 Announce Type: replace Abstract: LLM-based reviewing systems typically take only the manuscript as input, leaving literature and code-based claims hard to verify. We present FactRev

Falsification-driven reinforcement learning for maritime motion planning

arXiv:2510.06970v2 Announce Type: replace-cross Abstract: Compliance with maritime traffic rules is essential for the safe operation of autonomous vessels, yet training reinforcement learning (RL) age

agentsarxiv-cs-lg

Tutorials

Fascinating results + Anthropic running away with it right now + So many people want to start their own company + Google over OpenAI + Verce…

tutorialsjeremy-howard--x

Fascinating results + Anthropic running away with it right now + So many people want to start their own company + Google over OpenAI + Vercel, Linear, Every, PostHog overperforming A great list if you

Fast KV Compaction via Attention Matching

arXiv:2602.16284v2 Announce Type: replace Abstract: Scaling language models to long contexts is often bottlenecked by the size of the key-value (KV) cache. In deployed settings, long contexts are typi

Faster Thermal Profiling of a Lunar Rover with Machine Learning Adapted Finite Difference Model

arXiv:2605.27651v1 Announce Type: new Abstract: Autonomous space systems operating in extreme thermal environments require accurate and efficient thermal modeling to support both pre-mission system de

agentsarxiv-cs-lg

FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models

arXiv:2512.16483v2 Announce Type: replace Abstract: Visual Autoregressive (VAR) modeling departs from the next-token prediction paradigm of traditional Autoregressive (AR) models through next-scale pr

researcharxiv-cs-cv

FBI says Google engineer used internal search data to win $1.2M on Polymarket

Federal prosecutors charged a Google software engineer with making roughly $1.2 million in profits from bets on the prediction market platform Polymarket by using confidential insider information he l

industryars-technica

Local Ai

FD-RAG: Federated Dual-System Retrieval-Augmented Generation

arXiv:2605.27432v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) has emerged as a paradigm for grounding large language models in external knowledge, yet most existing RAG system

local-aiarxiv-cs-ai

FEA-SLT: A Gloss-Free End-to-End Framework for Facial-Expression-Aware Sign Language Translation

arXiv:2601.03549v2 Announce Type: replace-cross Abstract: Sign Language Translation (SLT) is a challenging cross-modal task requiring joint modeling of manual articulations and non-manual signals. Exi

researcharxiv-cs-cl

Fed up with vibe coders, dev sneaks data-nuking prompt injection into their code

A developer added hidden prompt injection instructions to jqwik, a Java testing app, to sabotage projects created by AI coding agents in response to the 'vibe coding' controversy. The incident represe

industryars-technica

FedEHR-Gen: Federated Synthetic Time-Series EHR Generation via Latent Space Alignment and Distribution-Aware Aggregation

arXiv:2605.27892v1 Announce Type: new Abstract: Synthetic Electronic Health Record (EHR) generation provides a promising avenue for data augmentation and cross-hospital modeling in privacy-constrained

safetyarxiv-cs-lg

Federated Learning for Multivariate Time Series Anomaly Detection in Industrial Automation

model-releasesarxiv-cs-lg

arXiv:2605.27486v1 Announce Type: new Abstract: Federated learning (FL) has broadened the horizon for multivariate time series anomaly detection (MTSAD). However, benchmarking such anomaly detection m

FedMPT: Federated Multi-label Prompt Tuning of Vision-Language Models

arXiv:2605.28347v1 Announce Type: new Abstract: Multi-Label Recognition (MLR) based on Vision-Language Models (VLMs) aims to leverage their pre-trained knowledge to better adapt complex recognition sc

Field evaluation and optimization of a lightweight autonomous lidar-based UAV system based on a rigorous experimental setup in boreal forest environments

arXiv:2512.14340v3 Announce Type: replace Abstract: Interest in utilizing autonomous uncrewed aerial vehicles (UAVs) for under-canopy forest remote sensing has increased in recent years, resulting in

agentsarxiv-cs-ro

FinBoardBench: Benchmarking Dynamic Wealth Management and Strategic Financial Reasoning of LLMs via Board Game Simulations

arXiv:2605.27896v1 Announce Type: new Abstract: Recently, large language models (LLMs) have achieved superior performance in static financial reasoning and simple dynamic trading tasks. However, exist

applicationsarxiv-cs-cl

Finding Miscompiles for Fun, Not Profit

model-releasessemianalysis

This article likely discusses the discovery and analysis of compiler bugs or miscompilation errors in software development tools, exploring how developers identify these issues and their implications

Finding Miscompiles for Fun, Not Profit Or: You don’t need access to Claude Mythos to spend $10,000 in an afternoon https://newsletter.semia…

model-releasesdylan-patel--x

This post discusses how compiler bugs or miscompiles can be discovered and exploited without expensive AI systems, illustrating that significant computational costs can be incurred quickly when identi

Fine-Tuned LLM as a Complementary Predictor Improving Ads System

arXiv:2605.27856v1 Announce Type: cross Abstract: Recommendation systems power engagement and monetization across feeds, ads, and short-video platforms, but translating the latest advances in Large La

applicationsarxiv-cs-ai

Fine-Tuning Dynamics of In-Context Factual Recall in Transformers

arXiv:2605.27774v1 Announce Type: new Abstract: In-context learning -- performing tasks based on examples given in the prompt -- is an important capability that has emerged in large language models an

Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent

arXiv:2605.27452v1 Announce Type: new Abstract: Bridge inspection in Japan requires mandatory visual assessments every five years, yet qualitative damage ratings (levels a-e) assigned by different eng

agentsarxiv-cs-cv

FinTexTS: Financial Text-Paired Time-Series Dataset via Semantic-Based and Multi-Level Pairing

arXiv:2603.02702v3 Announce Type: replace Abstract: The financial domain involves a variety of important time-series problems. Recently, time-series analysis methods that jointly leverage textual and

researcharxiv-cs-ai

Fitting Unknown Number of Hyperplanes with Manifold Optimization

arXiv:2605.28501v1 Announce Type: new Abstract: Fitting an unknown number of hyperplanes to data is a fundamental yet challenging problem in machine learning, characterized by its non-convexity, non-d

Flatness-Aware Stochastic Gradient Langevin Dynamics

arXiv:2510.02174v3 Announce Type: replace Abstract: Flatness of the loss landscape has been widely studied as an important perspective for understanding the behavior and generalization of deep learnin

FLORO: A Multimodal Geospatial Foundation Model for Ecological Remote Sensing Across Sensors and Scales

arXiv:2605.28174v1 Announce Type: cross Abstract: Foundation models offer a promising route to transferable remote sensing representations, but many current approaches depend on very large pretraining

FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation

arXiv:2605.21832v2 Announce Type: replace Abstract: Modern recommender systems rely heavily on ID-based collaborative filtering: each item is represented by a unique ID embedding that accumulates coll

applicationsarxiv-cs-ai

Fonoa, which helps enterprises manage indirect tax compliance, raised a $110M Series C led by Headline and acquired PwC's Indirect Tax Edge platform (Ryan Lawler/Axios)

Ryan Lawler / Axios: Fonoa, which helps enterprises manage indirect tax compliance, raised a 110M Series C led by Headline and acquired PwC's Indirect Tax Edge platform — Fonoa, which helps enterprise

industrytechmeme

Forecasters predict below-average hurricane season, advise against complacency

NOAA forecasts a 55% chance of a below-normal 2026 Atlantic hurricane season (June 1 - November 30) with 8-14 named storms, 3-6 hurricanes, and 1-3 major hurricanes. The below-average forecast is driv

industryars-technica

ForestHG-Trace: Traceable Long-Horizon Ecological Reasoning over Large-Scale Forest Scenes

model-releasesarxiv-cs-cv

arXiv:2605.27590v1 Announce Type: new Abstract: Remote sensing question answering (RS-QA) often requires more than direct semantic prediction, especially in large-scale forest scenes where ecological

Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models

arXiv:2510.17620v2 Announce Type: replace Abstract: Large language models may encode sensitive information or outdated knowledge that needs to be removed, to ensure responsible and compliant model res

researcharxiv-cs-cl