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From Table to Cell: Attention for Better Reasoning with TABALIGN

arXiv:2605.14465v1 Announce Type: new Abstract: Multi-step LLM reasoning over structured tables fails because planning and execution share no explicit cell-grounding contract. Existing methods constra

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From Text to Voice: A Reproducible and Verifiable Framework for Evaluating Tool Calling LLM Agents

DGX agent

arXiv:2605.15104v1 Announce Type: new Abstract: Voice agents increasingly require reliable tool use from speech, whereas prominent tool-calling benchmarks remain text-based. We study whether verified

model-releasesarxiv-cs-cl

15 May 2026

From User Preferences to Base Score Extraction Functions in Gradual Argumentation (with Appendix)

arXiv:2602.14674v4 Announce Type: replace Abstract: Gradual argumentation is a field of symbolic AI which is attracting attention for its ability to support transparent and contestable AI systems. It

Applications

FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale

arXiv:2605.14445v1 Announce Type: new Abstract: Many real-world coding challenges are open-ended and admit no known optimal solution. Yet, recent progress in LLM coding has focused on well-defined tas

applicationsarxiv-cs-lg

FU-MPC: Frontier- and Uncertainty-Aware Model Predictive Control for Efficient and Accurate UAV Exploration with Motorized LiDAR

arXiv:2605.14920v1 Announce Type: new Abstract: Efficient UAV exploration in unknown environments requires rapid coverage expansion while maintaining accurate and reliable localization, since safe nav

researcharxiv-cs-ro

Fully Dynamic Rebalancing in Dockless Bike-Sharing Systems via Deep Reinforcement Learning

arXiv:2605.14501v1 Announce Type: cross Abstract: This paper proposes a fully dynamic Deep Reinforcement Learning (DRL) method for rebalancing dockless bike-sharing systems, overcoming the limitations

Fun interview with Jacob Effron on the Unsupervised Learning podcast.

Fun interview with Jacob Effron on the Unsupervised Learning podcast. It’s hard to imagine more of a dream Unsupervised Learning guest than @ylecun. Yann is one of the godfathers of AI, and he has som

researchyann-lecun--x

Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs

arXiv:2410.06431v5 Announce Type: replace Abstract: Accurate uncertainty quantification in large language models (LLMs) is essential for reliable confidence estimation, yet fine-tuned LLMs often becom

researcharxiv-cs-lg

Further Notes on Our Recent Research on AI Delegation and Long-Horizon Reliability

researchmicrosoft-research

Our recent paper, “LLMs Corrupt Your Documents When You Delegate”, has generated discussion about the reliability of AI systems in delegated workflows. We appreciate the interest in this work and want

Fusion-fission forecasts when AI will shift to undesirable behavior

arXiv:2605.14218v1 Announce Type: new Abstract: The key problem facing ChatGPT-like AI's use across society is that its behavior can shift, unnoticed, from desirable to undesirable -- encouraging self

FutureSim: Replaying World Events to Evaluate Adaptive Agents

arXiv:2605.15188v1 Announce Type: cross Abstract: AI agents are being increasingly deployed in dynamic, open-ended environments that require adapting to new information as it arrives. To efficiently m

G-SHARP: Gaussian Surgical Hardware Accelerated Real-time Pipeline

model-releasesarxiv-cs-cv

arXiv:2512.02482v2 Announce Type: replace Abstract: We propose G-SHARP, a commercially compatible, real-time surgical scene reconstruction framework designed for minimally invasive procedures that req

@GaryMarcus If token prediction is 'generating thought itself,' then my phone's autocomplete is a philosopher.

Gary Marcus critiques the claim that token prediction in large language models constitutes genuine thought or reasoning, using the analogy of smartphone autocomplete to illustrate that predictive text

safetygary-marcus--x

GEAR: Genetic AutoResearch for Agentic Code Evolution

arXiv:2605.13874v1 Announce Type: cross Abstract: Autonomous research agents can already run machine learning experiments without human supervision, but many rely on a narrow search strategy: they rep

Gemini Live Agent Challenge: Announcing the winners and highlights

model-releasesgoogle-cloud-ai

The Gemini Live Agent Challenge is officially in the books! We challenged developers worldwide to break out of the traditional 'text box' paradigm by building next-generation AI agents. From our initi

Gemma-4-31B-it-Pearl supports 256K context, configurable thinking, function calling, and JSON mode. This is Together AI’s first Pearl-powere…

model-releasestogether-ai--x

Gemma-4-31B-it-Pearl supports 256K context, configurable thinking, function calling, and JSON mode. This is Together AI’s first Pearl-powered endpoint. Eventually, we plan to expand our Pearl powered

Gemma-4-31B-it-Pearl supports text and image input, 256K context, configurable thinking, function calling, and JSON mode. This is Together A…

model-releasestogether-ai--x

Gemma-4-31B-it-Pearl supports text and image input, 256K context, configurable thinking, function calling, and JSON mode. This is Together AI’s first Pearl-powered endpoint. Eventually, we plan to exp

Hardware

GenAI for Energy-Efficient and Interference-Aware Compressed Sensing of GNSS Signals on a Google Edge TPU

arXiv:2605.14839v1 Announce Type: new Abstract: Traditional methods for classifying global navigation satellite system (GNSS) jamming signals typically involve post-processing raw or spectral data str

hardwarearxiv-cs-lg

GenCircuit-RL: Reinforcement Learning from Hierarchical Verification for Genetic Circuit Design

arXiv:2605.14215v1 Announce Type: new Abstract: Genetic circuit design remains a laborious, expert-driven process despite decades of progress in synthetic biology. We study this problem through code g

Generalized Priority-Aware Shapley Value

arXiv:2605.15018v1 Announce Type: cross Abstract: Shapley value and its priority-aware extensions are widely used for valuation in machine learning, but existing methods require pairwise priority to b

Generalizing Score-based generative models for Heavy-tailed Distributions

arXiv:2603.00772v2 Announce Type: replace-cross Abstract: Score-based generative models (SGMs) have achieved remarkable empirical success, motivating their application to a broad range of data distrib

researcharxiv-cs-lg

Generating HDR Video from SDR Video

arXiv:2605.14703v1 Announce Type: new Abstract: The high dynamic range (HDR) video ecosystem is approaching maturity, but the problem of upconverting legacy standard dynamic range (SDR) videos persist

researcharxiv-cs-cv

Generative Bayesian Optimization: Generative Models as Acquisition Functions

arXiv:2510.25240v3 Announce Type: replace-cross Abstract: We present a general strategy for turning generative models into candidate solution samplers for batch Bayesian optimization (BO). The use of

researcharxiv-cs-lg

Generative Deep Learning for Computational Destaining and Restaining of Unregistered Digital Pathology Images

arXiv:2605.14251v1 Announce Type: new Abstract: Conditional generative adversarial networks (cGANs) have enabled high-fidelity computational staining and destaining of hematoxylin and eosin (H&E) in d

safetyarxiv-cs-cv

Generative Floor Plan Design with LLMs via Reinforcement Learning with Verifiable Rewards

arXiv:2605.14117v1 Announce Type: cross Abstract: An AI system for professional floor plan design must precisely control room dimensions and areas while respecting the desired connectivity between roo

GenExam: A Multidisciplinary Text-to-Image Exam

model-releasesarxiv-cs-cv

arXiv:2509.14232v5 Announce Type: replace Abstract: Exams are a fundamental test of expert-level intelligence and require integrated understanding, reasoning, and generation. Existing exam-style bench

Geometry-Aware Decoding with Wasserstein-Regularized Truncation and Mass Penalties for Large Language Models

arXiv:2602.10346v2 Announce Type: replace Abstract: Large language models (LLMs) must balance diversity and creativity against logical coherence in open-ended generation. Existing truncation-based sam

researcharxiv-cs-cl

Geometry-Aware Sampling-Based Motion Planning on Riemannian Manifolds

arXiv:2602.00992v2 Announce Type: replace Abstract: In many robot motion planning problems, task objectives and physical constraints induce non-Euclidean geometry on the configuration space, yet many

researcharxiv-cs-ro

Local Ai

GeoViSTA: Geospatial Vision-Tabular Transformer for Multimodal Environment Representation

arXiv:2605.14406v1 Announce Type: cross Abstract: Large-scale pretraining on Earth observation imagery has yielded powerful representations of the natural and built environment. However, most existing

local-aiarxiv-cs-cv

Local Ai

GeoVista: Visually Grounded Active Perception for Ultra-High-Resolution Remote Sensing Understanding

arXiv:2605.14475v1 Announce Type: new Abstract: Interpreting ultra-high-resolution (UHR) remote sensing images requires models to search for sparse and tiny visual evidence across large-scale scenes.

local-aiarxiv-cs-cv

GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning

model-releasesarxiv-cs-lg

arXiv:2605.14809v1 Announce Type: new Abstract: Graph prompt tuning has shown great potential in graph learning by introducing trainable prompts to enhance the model performance in conventional single

GhostCite: A Large-Scale Analysis of Citation Validity in the Age of Large Language Models

arXiv:2602.06718v2 Announce Type: replace-cross Abstract: Citations provide the basis for trusting scientific claims; when they are invalid or fabricated, this trust collapses. With the advent of Larg

Go in with expectations that Grok Build is still beta, but improving almost every day

Go in with expectations that Grok Build is still beta, but improving almost every day Grok Build is amazing. The early beta just dropped for SuperGrok Heavy users and the first real feedback from deve

agentselon-musk--x

Good to Go: The LOOP Skill Engine That Hits 99% Success and Slashes Token Usage by 99% via One-Shot Recording and Deterministic Replay

arXiv:2605.14237v1 Announce Type: new Abstract: Deploying AI agents for repetitive periodic tasks exposes a critical tension: Large Language Models (LLMs) offer unmatched flexibility in tool orchestra

Google confirms it's testing a new storage policy after some users reported that new Gmail accounts get only 5GB of free storage unless they add a phone number (Akshay Gangwar/Android Authority)

Akshay Gangwar / Android Authority: Google confirms it's testing a new storage policy after some users reported that new Gmail accounts get only 5GB of free storage unless they add a phone number — Up

safetytechmeme

Google updates its spam rules to include attempts to ‘manipulate’ AI

Google updated its spam policy to mark attempts to 'manipulate' its AI model in search results as spam, including results in AI Overview or AI Mode in Search, as Search Engine Land reports: 'In the co

safetythe-verge-ai

GPart: End-to-End Isometric Fine-Tuning via Global Parameter Partitioning

arXiv:2605.14841v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) has become the dominant paradigm for parameter-efficient fine-tuning (PEFT) of large language models (LLMs). However, its b

Gradient Iterated Temporal-Difference Learning

arXiv:2603.07833v2 Announce Type: replace-cross Abstract: Temporal-difference (TD) learning is highly effective at controlling and evaluating an agent's long-term outcomes. Most approaches in this par

GradShield: Alignment Preserving Finetuning

arXiv:2605.14194v1 Announce Type: new Abstract: Large Language Models (LLMs) pose a significant risk of safety misalignment after finetuning, as models can be compromised by both explicitly and implic

safetyarxiv-cs-cl

Graph of States: Solving Abductive Tasks with Large Language Models

arXiv:2603.21250v2 Announce Type: replace Abstract: Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former

GraphBit: A Graph-based Agentic Framework for Non-Linear Agent Orchestration

arXiv:2605.13848v1 Announce Type: new Abstract: Agentic LLM frameworks that rely on prompted orchestration, where the model itself determines workflow transitions, often suffer from hallucinated routi

Local Ai

GraphFlow: An Architecture for Formally Verifiable Visual Workflows Enabling Reliable Agentic AI Automation

arXiv:2605.14968v1 Announce Type: new Abstract: GraphFlow is a visual workflow system designed to improve the reliability of agentic AI automation in multi-step, mission-critical processes. In these w

local-aiarxiv-cs-ai

Graphs of Research: Citation Evolution Graphs as Supervision for Research Idea Generation

arXiv:2605.14790v1 Announce Type: cross Abstract: Research idea generation is the innovation-driving step of automated scientific research. Recently, large language models (LLMs) have shown potential

Great paper discussing agentic search vs. vector search.

Great paper discussing agentic search vs. vector search. // Is Grep All You Need? // Pay attention to this on, AI devs. (bookmark it) They find that grep-style text search, when wrapped in the right a

agentsdair-ai--x

Hardware

GridCare raises $64M to speed up AI data center projects

GridCare Inc., a startup that helps data center operators more quickly connect their facilities to the electrical grid, has raised 64 million in funding. Early Nvidia Corp. backer Sutter Hill Ventures

hardwaresiliconangle

Industry

Gridcare, which uses AI to detect underused capacity in electric grids, raised a 64M Series A, following a 13.5M seed in 2025 (Bianca Giacobone/Latitude Media)

Bianca Giacobone / Latitude Media: Gridcare, which uses AI to detect underused capacity in electric grids, raised a 64M Series A, following a 13.5M seed in 2025 — The grid intelligence startup uses AI

industrytechmeme

Grokking Finite-Dimensional Algebra

arXiv:2602.19533v2 Announce Type: replace-cross Abstract: This paper investigates the grokking phenomenon, which refers to the sudden transition from a long memorization to generalization observed dur

safetyarxiv-cs-ai

Grounded Continuation: A Linear-Time Runtime Verifier for LLM Conversations

arXiv:2605.14175v1 Announce Type: new Abstract: In long conversations, an LLM can produce a next utterance that sounds plausible but rests on premises the conversation has already abandoned. Context-m