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Experiments or Outcomes? Probing Scientific Feasibility in Large Language Models

arXiv:2604.18786v1 Announce Type: cross Abstract: Scientific feasibility assessment asks whether a claim is consistent with established knowledge and whether experimental evidence could support or ref

researcharxiv-cs-ai

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ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors

DGX agent

arXiv:2603.15956v2 Announce Type: replace-cross Abstract: Learning generalizable and robust behavior cloning policies requires large volumes of high-quality robotics data. While human demonstrations (

safetyarxiv-cs-ai

22 Apr 2026

Explicit Trait Inference for Multi-Agent Coordination

arXiv:2604.19278v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) show promise on complex tasks but remain prone to coordination failures such as goal drift, error cascades, and misa

agentsarxiv-cs-ai

Explore Like Humans: Autonomous Exploration with Online SG-Memo Construction for Embodied Agents

arXiv:2604.19034v1 Announce Type: new Abstract: Constructing structured spatial memory is essential for enabling long-horizon reasoning in complex embodied navigation tasks. Current memory constructio

agentsarxiv-cs-cv

Exploring Language-Agnosticity in Function Vectors: A Case Study in Machine Translation

arXiv:2604.19678v1 Announce Type: new Abstract: Function vectors (FVs) are vector representations of tasks extracted from model activations during in-context learning. While prior work has shown that

applicationsarxiv-cs-cl

Face Anything: 4D Face Reconstruction from Any Image Sequence

arXiv:2604.19702v1 Announce Type: new Abstract: Accurate reconstruction and tracking of dynamic human faces from image sequences is challenging because non-rigid deformations, expression changes, and

researcharxiv-cs-cv

Failure Modes in Multi-Hop QA: The Weakest Link Effect and the Recognition Bottleneck

arXiv:2601.12499v2 Announce Type: replace Abstract: Despite scaling to massive context windows, Large Language Models (LLMs) struggle with multi-hop reasoning due to inherent position bias, which caus

Fairness Audits of Institutional Risk Models in Deployed ML Pipelines

arXiv:2604.19468v1 Announce Type: cross Abstract: Fairness audits of institutional risk models are critical for understanding how deployed machine learning pipelines allocate resources. Drawing on mul

FairTree: Subgroup Fairness Auditing of Machine Learning Models with Bias-Variance Decomposition

arXiv:2604.19357v1 Announce Type: new Abstract: The evaluation of machine learning models typically relies mainly on performance metrics based on loss functions, which risk to overlook changes in perf

Fascinating how AI is getting better at diagrams like these (at least for ones that you could easily find on web search) but still making so…

Fascinating how AI is getting better at diagrams like these (at least for ones that you could easily find on web search) but still making some pretty wacky errors — like confusing where the rear brake

safetygary-marcus--x

FASE : A Fairness-Aware Spatiotemporal Event Graph Framework for Predictive Policing

arXiv:2604.18644v1 Announce Type: cross Abstract: Predictive policing systems that allocate patrol resources based solely on predicted crime risk can unintentionally amplify racial disparities through

Fast and Robust Diffusion Posterior Sampling for MR Image Reconstruction Using the Preconditioned Unadjusted Langevin Algorithm

model-releasesarxiv-cs-cv

arXiv:2512.05791v2 Announce Type: replace-cross Abstract: Purpose: The Unadjusted Langevin Algorithm (ULA) in combination with diffusion models can generate high quality MRI reconstructions with uncer

Fast estimation of Gaussian mixture components via centering and singular value thresholding

arXiv:2604.19091v1 Announce Type: cross Abstract: Estimating the number of components is a fundamental challenge in unsupervised learning, particularly when dealing with high-dimensional data with man

researcharxiv-cs-lg

FASTER: Value-Guided Sampling for Fast RL

arXiv:2604.19730v1 Announce Type: cross Abstract: Some of the most performant reinforcement learning algorithms today can be prohibitively expensive as they use test-time scaling methods such as sampl

FB-NLL: A Feature-Based Approach to Tackle Noisy Labels in Personalized Federated Learning

arXiv:2604.19729v1 Announce Type: new Abstract: Personalized Federated Learning (PFL) aims to learn multiple task-specific models rather than a single global model across heterogeneous data distributi

Feasibility of Indoor Frame-Wise Lidar Semantic Segmentation via Distillation from Visual Foundation Model

arXiv:2604.18831v1 Announce Type: new Abstract: Frame-wise semantic segmentation of indoor lidar scans is a fundamental step toward higher-level 3D scene understanding and mapping applications. Howeve

agentsarxiv-cs-cv

Feature Perturbation Pool-based Fusion Network for Unified Multi-Class Industrial Defect Detection

arXiv:2604.19259v1 Announce Type: new Abstract: Multi-class defect detection constitutes a critical yet challenging task in industrial quality inspection, where existing approaches typically suffer fr

researcharxiv-cs-cv

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion

arXiv:2604.19015v1 Announce Type: cross Abstract: Federated fine-tuning of Large Language Models (LLMs) is obstructed by a trilemma of challenges: protecting LLMs intellectual property (IP), ensuring

FedSEA: Achieving Benefit of Parallelization in Federated Online Learning

arXiv:2604.19336v1 Announce Type: new Abstract: Online federated learning (OFL) has emerged as a popular framework for decentralized decision-making over continuous data streams without compromising c

researcharxiv-cs-lg

FG^2-GDN: Enhancing Long-Context Gated Delta Networks with Doubly Fine-Grained Control

arXiv:2604.19021v1 Announce Type: new Abstract: Linear attention mechanisms have emerged as promising alternatives to softmax attention, offering linear-time complexity during inference. Recent advanc

applicationsarxiv-cs-lg

Tools

File upsert is now live in Pinecone Assistant. Create or replace files by a custom ID you define — no UUID tracking. Upload, upsert, and del…

File upsert is now live in Pinecone Assistant. Create or replace files by a custom ID you define — no UUID tracking. Upload, upsert, and delete return a pollable operation object. List and describe fi

toolspinecone--x

Filing: Tron founder Justin Sun sues the Trump family's World Liberty Financial, alleging it unfairly locked up his WLFI holdings and threatened and defamed him (CoinDesk)

CoinDesk: Filing: Tron founder Justin Sun sues the Trump family's World Liberty Financial, alleging it unfairly locked up his WLFI holdings and threatened and defamed him — World Liberty unfairly froz

safetytechmeme

Fine-Tuning Code Language Models to Detect Cross-Language Bugs

arXiv:2507.21954v2 Announce Type: replace-cross Abstract: Multilingual programming, which involves using multiple programming languages (PLs) in a single project, is increasingly common due to its ben

researcharxiv-cs-ai

Fine-tuning DeepSeek-OCR-2 for Molecular Structure Recognition

arXiv:2604.03476v2 Announce Type: replace-cross Abstract: Optical Chemical Structure Recognition (OCSR) is critical for converting 2D molecular diagrams from printed literature into machine-readable f

Fine-Tuning Small Reasoning Models for Quantum Field Theory

arXiv:2604.18936v1 Announce Type: cross Abstract: Despite the growing application of Large Language Models (LLMs) to theoretical physics, there is little academic exploration into how domain-specific

Finite-dimensional approximations of push-forwards on locally analytic functionals

arXiv:2404.10769v4 Announce Type: replace-cross Abstract: This paper develops a functional-analytic framework for approximating the push-forward induced by an analytic map from finitely many samples.

researcharxiv-cs-lg

Fitted Q Evaluation Without Bellman Completeness via Stationary Weighting

arXiv:2512.23805v2 Announce Type: replace-cross Abstract: Fitted Q-evaluation (FQE) is a foundational method for off-policy evaluation in reinforcement learning, but existing theory typically relies o

Industry

Florida attorney general issues subpoenas in ChatGPT probe over FSU shooting

Florida Attorney General James Uthmeier today said that the state has opened a criminal investigation into ChatGPT and its parent company, OpenAI Group PBC, over whether the company bears any criminal

industrysiliconangle

Local Ai

FlowForge: A Staged Local Rollout Engine for Flow-Field Prediction

arXiv:2604.18953v1 Announce Type: new Abstract: Deep learning surrogates for CFD flow-field prediction often rely on large, complex models, which can be slow and fragile when data are noisy or incompl

local-aiarxiv-cs-lg

FluentAvatar: Flicker-Free Talking-Head Animation via Phoneme-Guided Autoregressive Modeling

model-releasesarxiv-cs-cv

arXiv:2509.12052v3 Announce Type: replace Abstract: Current talking-head generation has gradually shifted from GAN-based methods to diffusion-based paradigms, achieving remarkable progress in visual f

Local Ai

Flux 2-Klein-9B NVFP4 works well on my RTX 3050, but it takes 55sec to generate 1024 resolution.

local-air-stablediffusion

Flux 2-Klein-9B NVFP4 is a quantized image generation model that runs on mid-range GPUs like the RTX 3050. On this hardware, the model produces 1024-resolution images but with relatively slow inferenc

Tutorials

FOCAL-Attention for Heterogeneous Multi-Label Prediction

arXiv:2604.19171v1 Announce Type: new Abstract: Heterogeneous graphs have attracted increasing attention for modeling multi-typed entities and relations in complex real-world systems. Multi-label node

tutorialsarxiv-cs-lg

Tutorials

FoNE: Precise Single-Token Number Embeddings via Fourier Features

arXiv:2502.09741v2 Announce Type: replace Abstract: Large Language Models (LLMs) typically represent numbers using multiple tokens, which requires the model to aggregate these tokens to interpret nume

tutorialsarxiv-cs-cl

For real agentic workloads (North), short-context calibration wasn't enough. We calibrated AWQ on long internal agentic traces (up to 64k to…

For real agentic workloads (North), short-context calibration wasn't enough. We calibrated AWQ on long internal agentic traces (up to 64k tokens) and added token masking in llm-compressor to exclude r

agentscohere--x

For the 'small test' they've modified their docs to remove mention of Claude Code in Claude Pro: https://support.claude.com/en/articles/1114…

model-releasesjeremy-howard--x

For the 'small test' they've modified their docs to remove mention of Claude Code in Claude Pro: https://support.claude.com/en/articles/11145838-using-claude-code-with-your-max-plan It's been a shock

Industry

For years, the Left said 'replacement migration' was a 'conspiracy theory,' but as it turns out, it was a real conspiracy led by Gavin Newso…

For years, the Left said 'replacement migration' was a 'conspiracy theory,' but as it turns out, it was a real conspiracy led by Gavin Newsom, the State of California, and a circle of radical left-win

industryelon-musk--x

Formally Verified Patent Analysis via Dependent Type Theory: Machine-Checkable Certificates from a Hybrid AI + Lean 4 Pipeline

arXiv:2604.18882v1 Announce Type: new Abstract: We present a formally verified framework for patent analysis as a hybrid AI + Lean 4 pipeline. The DAG-coverage core (Algorithm 1b) is fully machine-ver

applicationsarxiv-cs-ai

Forward Dynamics of Variable Topology Mechanisms - The Case of Constraint Activation

arXiv:2604.19419v1 Announce Type: new Abstract: Many mechanical systems exhibit changes in their kinematic topology altering the mobility. Ideal contact is the best known cause, but also stiction and

researcharxiv-cs-ro

Four-Axis Decision Alignment for Long-Horizon Enterprise AI Agents

arXiv:2604.19457v1 Announce Type: new Abstract: Long-horizon enterprise agents make high-stakes decisions (loan underwriting, claims adjudication, clinical review, prior authorization) under lossy mem

Framelet-Based Blind Image Restoration with Minimax Concave Regularization

arXiv:2604.19314v1 Announce Type: new Abstract: Recovering corrupted images is one of the most challenging problems in image processing. Among various restoration tasks, blind image deblurring has bee

safetyarxiv-cs-cv

From Craft to Kernel: A Governance-First Execution Architecture and Semantic ISA for Agentic Computers

arXiv:2604.18652v1 Announce Type: cross Abstract: The transition of agentic AI from brittle prototypes to production systems is stalled by a pervasive crisis of craft. We suggest that the prevailing o

agentsarxiv-cs-ai

From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning

arXiv:2604.19516v1 Announce Type: new Abstract: Generative engines (GEs) are reshaping information access by replacing ranked links with citation-grounded answers, yet current Generative Engine Optimi

Local Ai

From Local to Production: The Complete Developer Journey for Building, Composing, and Deploying AI Agents

local-aimicrosoft-foundry

When we launched Microsoft Agent Framework last October, we made a promise: building production-grade AI agents should feel as natural and structured as building any other software. Today, we’re deliv

From Natural Language to Executable Narsese: A Neuro-Symbolic Benchmark and Pipeline for Reasoning with NARS

arXiv:2604.18873v1 Announce Type: new Abstract: Large language models (LLMs) are highly capable at language generation, but they remain unreliable when reasoning requires explicit symbolic structure,

From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing

arXiv:2604.18918v1 Announce Type: cross Abstract: Simulation-based testing of autonomous driving systems (ADS) must uncover realistic and diverse failures in dense, heterogeneous traffic. However, exi

From Proof to Program: Characterizing Tool-Induced Reasoning Hallucinations in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2511.10899v2 Announce Type: replace Abstract: Tool-augmented Language Models (TaLMs) can invoke external tools to solve problems beyond their parametric capacity. However, it remains unclear whe

Hardware

From Rainforests to Recycling Plants: 5 Ways NVIDIA AI Is Protecting the Planet

NVIDIA AI and accelerated computing are advancing sustainability, climate science and energy efficiency through five key applications. These include RecycleOS, an AI and robotics solution that helps r

hardwarenvidia-blog

From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems

arXiv:2604.19663v1 Announce Type: cross Abstract: Counterfactual explanations (CEs) provide an intuitive way to understand recommender systems by identifying minimal modifications to user-item interac

applicationsarxiv-cs-lg