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Evidence-Guided Unknown Rejection for High-Confidence Near-Known Unknowns

arXiv:2605.17818v1 Announce Type: new Abstract: Open-set recognition systems face a neglected failure mode: high-confidence near-known unknowns, which lie outside the known label set but are close eno

researcharxiv-cs-cv

Tutorials

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Evidence of a Cognitive Shift in AI Education: How Students Are Rethinking Human Intelligence?

DGX agent

arXiv:2605.16292v1 Announce Type: cross Abstract: Perceptions of intelligence shape how learners evaluate and rely on artificial intelligence (AI) systems. Despite rapid advances in AI capabilities, t

tutorialsarxiv-cs-ai

19 May 2026

Evidential Information Fusion on Possibilistic Structure

arXiv:2605.17038v1 Announce Type: new Abstract: Dempster's rule is a fundamental tool for combining belief functions from distinct and reliable sources. However, its intersection-based semantics impos

EvilGenie: A Reward Hacking Benchmark

model-releasesarxiv-cs-lg

arXiv:2511.21654v2 Announce Type: replace Abstract: We introduce EvilGenie, a benchmark for reward hacking in programming settings. We source problems from LiveCodeBench and create an environment in w

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory

arXiv:2511.20857v2 Announce Type: replace-cross Abstract: Statefulness is essential for large language model (LLM) agents to perform long-term planning and problem-solving. This makes memory a critica

Evolutionary Extreme Learning Machine of ab-initio Energy Landscapes for Crystal Structure Prediction using Manta Ray Optimization with Levy Flight

arXiv:2605.17148v1 Announce Type: cross Abstract: The Manta Ray Foraging Optimization algorithm (MRFO) has proven to be a powerful heuristic strategy in the optimal solution of a large number of engin

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs

model-releasesarxiv-cs-cl

arXiv:2511.12710v2 Announce Type: replace Abstract: Automated red teaming frameworks for Large Language Models (LLMs) have become increasingly sophisticated, yet many still formulate attack optimizati

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective

arXiv:2605.18421v1 Announce Type: cross Abstract: Recent benchmarks for Large Language Model (LLM) agents mainly evaluate reasoning, planning, and execution. However, memory is also essential for agen

EvoQRE: Modeling Bounded Rationality in Safety-Critical Traffic Simulation via Evolutionary Quantal Response Equilibrium

model-releasesarxiv-cs-ro

arXiv:2601.05653v2 Announce Type: replace Abstract: Existing traffic simulation frameworks for autonomous vehicles typically rely on imitation learning or game-theoretic approaches that solve for Nash

Exact Convex Reformulations of Linear Neural Networks via Completely Positive Lifting

arXiv:2605.17692v1 Announce Type: new Abstract: We show that the training problem of a deep linear neural network under the squared loss admits an exact convex reformulation in a lifted space over a g

researcharxiv-cs-lg

Applications

Excited for this conversation with @hwchase17 , Co-Founder & CEO of @LangChain , on June 2 at the @traversal_ai office in NYC. We’ll be talk…

applicationsharrison-chase--x

Excited for this conversation with @hwchase17 , Co-Founder & CEO of @LangChain , on June 2 at the @traversal_ai office in NYC. We’ll be talking about what it actually takes to operate AI agents in pro

Excited to share our new paper: RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably LLMs often fail on inputs well wi…

Excited to share our new paper: RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably LLMs often fail on inputs well within their advertised context lengths. We show that these fa

agentsjeremy-howard--x

EXG: Self-Evolving Agents with Experience Graphs

arXiv:2605.17721v1 Announce Type: new Abstract: Large language model (LLM)-based agents have demonstrated strong capabilities in complex reasoning and problem solving through multi-step interactions,

agentsarxiv-cs-ai

Expandable, Compressible, Mineable: Open-World Thermal Image Restoration

model-releasesarxiv-cs-cv

arXiv:2605.16967v1 Announce Type: new Abstract: In open-world settings, thermal infrared (TIR) image degradations continuously emerge and evolve, while most existing all-in-one restoration methods are

Expectation and Acoustic Neural Network Representations Enhance Music Identification from Brain Activity

arXiv:2603.03190v3 Announce Type: replace Abstract: During music listening, cortical activity encodes both acoustic and expectation-related information. Prior work has shown that ANN representations r

Experiment-as-Code Labs: A Declarative Stack for AI-Driven Scientific Discovery

arXiv:2605.04375v2 Announce Type: replace-cross Abstract: To unleash the full potential of AI for Science, we must untether the agents from a purely digital environment. The agent's ability to control

safetyarxiv-cs-ai

Experimentally validated quantum-secure federated learning over a multi-user quantum network

arXiv:2501.12709v2 Announce Type: replace-cross Abstract: Federated learning enables decentralized, privacy-preserving training but remains vulnerable to privacy leakage in the quantum era. Quantum fe

Explaining Object Detectors via Collective Contribution of Pixels

arXiv:2412.00666v4 Announce Type: replace Abstract: Visual explanations for object detectors are crucial for enhancing their reliability. Object detectors identify and localize instances by assessing

researcharxiv-cs-cv

Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks

arXiv:2603.11689v2 Announce Type: replace Abstract: Frontier Multimodal Large Language Models (MLLMs) exhibit remarkable capabilities in Visual-Language Comprehension (VLC) tasks. However, they are of

Applications

Exploring Lightweight Large Language Models for Court View Generation

arXiv:2605.16770v1 Announce Type: cross Abstract: Criminal Court View Generation (CVG) is a critical task in Legal Artificial Intelligence (Legal AI), involving the generation of court view based on c

applicationsarxiv-cs-ai

Exploring Trust Calibration in XAI - The Impact of Exposing Model Limitations to Lay Users

arXiv:2605.18036v1 Announce Type: cross Abstract: Trust calibration -- aligning user trust judgment with model capability -- is crucial for safe deployment of explainable AI (XAI), yet is often evalua

Extending conversational memory in Kiro CLI using Amazon Bedrock AgentCore Memory

In this post, we demonstrate how you can extend the conversational memory of Kiro CLI by implementing a custom Model Context Protocol (MCP) server that integrates with Amazon Bedrock AgentCore Memory.

agentsaws-ml-blog

Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons

arXiv:2605.16975v1 Announce Type: cross Abstract: Electrocardiogram (ECG) foundation models pretrained on typical diagnostic 10-second ECG segments, have demonstrated strong transferability across a r

extit{Don't Guess, Just Ask}: Resolving Ambiguity in Referring Segmentation via Multi-turn Clarification

model-releasesarxiv-cs-cv

arXiv:2605.17531v1 Announce Type: new Abstract: Referring segmentation aims to segment the target objects in images or videos based on the textual query. Despite remarkable progress over the past year

Extracting latent representations from X-ray spectra. Classification, regression, and accretion signatures of Chandra sources

arXiv:2510.14102v2 Announce Type: replace-cross Abstract: Spectral signatures are crucial in the era of large X-ray surveys. Automatic machine learning methods have proven useful in this respect, but

extsc{MasFACT}: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer

arXiv:2605.17361v1 Announce Type: cross Abstract: Multi-agent systems (MAS) powered by large language models (LLMs) have emerged as a powerful paradigm for complex problem solving, where performance c

agentsarxiv-cs-ai

extsc{PrivScope}: Task-scoped Disclosure Control for Hybrid Agentic Systems

arXiv:2605.16630v1 Announce Type: cross Abstract: Hybrid local--cloud agents enrich user requests with context from persistent working state before delegating capability-intensive subtasks to a cloud

exttt{SynC}: Synergistic Boosting of Structure and Representation for Deep Graph Clustering

arXiv:2406.15797v2 Announce Type: replace-cross Abstract: Employing graph neural networks (GNNs) for graph clustering has shown promising results in deep graph clustering. However, existing methods di

F2IND-IT! -- Multimodal Fuzzy Fake Indian News Detection using Images and Text

arXiv:2605.17115v1 Announce Type: new Abstract: Biased manipulation of facts across regional and national media outlets complicates misinformation detection in diverse landscapes like India. This pape

Face inpainting with Identity Preserving Latent Diffusion Models

arXiv:2605.16696v1 Announce Type: new Abstract: Face inpainting techniques recover missing or occluded facial regions in a visually realistic manner, but preserving the identity in the final output re

safetyarxiv-cs-cv

Factored Causal Representation Learning for Robust Reward Modeling in RLHF

arXiv:2601.21350v2 Announce Type: replace Abstract: A reliable reward model is essential for aligning large language models with human preferences through reinforcement learning from human feedback. H

safetyarxiv-cs-lg

Factorized Latent Dynamics for Video JEPA: An Empirical Study of Auxiliary Objectives

arXiv:2605.17165v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPA) are a promising framework for self-supervised video representation learning, yet the behavior of auxilia

researcharxiv-cs-cv

Factual Inconsistencies in Multilingual Wikipedia Tables

arXiv:2507.18406v2 Announce Type: replace Abstract: Wikipedia serves as a globally accessible knowledge source with content in over 300 languages. Despite covering the same topics, the different versi

safetyarxiv-cs-cl

Industry

Fair expectations

Fair expectations Does it make you “far right” to want: - vetted immigration - no digital ID - lower taxes - no two-tier policing - free speech - pedophiles out of office - lower cost of living MSM an

industryelon-musk--x

FAM-HRI: Foundation-Model Assisted Multi-Modal Human-Robot Interaction Combining Gaze and Speech

model-releasesarxiv-cs-ro

arXiv:2503.16492v3 Announce Type: replace-cross Abstract: ffective Human-Robot Interaction (HRI) is crucial for enhancing accessibility and usability in real-world robotics applications. However, exis

Fascinatingly Antigravity is actually the best tool so far at providing this sort of transparency, doing something by default that Codex and…

model-releasesethan-mollick--x

Fascinatingly Antigravity is actually the best tool so far at providing this sort of transparency, doing something by default that Codex and Code do not: offering a summary of exactly what it did at t

Fast Kernel-Space Diffusion for Remote Sensing Pansharpening

model-releasesarxiv-cs-cv

arXiv:2505.18991v3 Announce Type: replace Abstract: Pansharpening seeks to fuse high-resolution panchromatic (PAN) and low-resolution multispectral (LRMS) images into a single image with both fine spa

Fast Rates for Nonstationary Weighted Risk Minimization

arXiv:2602.05742v2 Announce Type: replace-cross Abstract: Weighted empirical risk minimization is a common approach to prediction under distribution drift. This article studies its out-of-sample predi

researcharxiv-cs-lg

Local Ai

FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing

arXiv:2605.17447v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have shown strong promise on Optical Character Recognition (OCR), yet the sheer number of visual tokens required to enco

local-aiarxiv-cs-cl

Industry

FBI seeks US-wide access to license plate cameras, wants 'data in near real time'

The FBI is seeking up to $36 million for nationwide access to automated license plate reader (ALPRs) data, which would allow it to query vehicle movements across the U.S. and its territories through a

industryars-technica

Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent

arXiv:2605.17767v1 Announce Type: cross Abstract: We study feature learning in two-layer neural networks within the linear-width regime, where the number of hidden neurons, sample size, and input dime

safetyarxiv-cs-lg

Applications

Federated Distillation on Edge Devices: Efficient Client-Side Filtering for Non-IID Data

arXiv:2508.14769v2 Announce Type: replace Abstract: Federated distillation has emerged as a promising collaborative machine learning approach, offering enhanced privacy protection and reduced communic

applicationsarxiv-cs-lg

Local Ai

Federated Learning by Utility-Constrained Stochastic Aggregation for Improving Rational Participation

arXiv:2605.18020v1 Announce Type: new Abstract: Federated Learning (FL) algorithms implicitly assume that clients passively comply with server-side orchestration by sharing local model updates upon se

local-aiarxiv-cs-lg

Federated Martingale Posterior Samping

model-releasesarxiv-cs-lg

arXiv:2605.18554v1 Announce Type: new Abstract: Federated Bayesian neural networks require fixing a prior on the model parameters together with a likelihood. Eliciting meaningful priors on the weight

Tutorials

Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation

arXiv:2605.16350v1 Announce Type: cross Abstract: We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules,

tutorialsarxiv-cs-ai

FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints

arXiv:2509.06984v3 Announce Type: replace-cross Abstract: Federated Learning with LoRA fine-tuning offers an efficient and privacy-aware solution for institutions to collaboratively leverage their lar

Local Ai

FedSDR: Federated Self-Distillation with Rectification

arXiv:2605.18028v1 Announce Type: cross Abstract: Federated fine-tuning of Large Language Models faces severe statistical heterogeneity. However, existing model-level defenses often overlook the root

local-aiarxiv-cs-ai

FEG-Pro: Forecast-Error Growth Profiling for Finite-Horizon Instability Analysis of Nonlinear Time Series

arXiv:2605.17282v1 Announce Type: cross Abstract: Estimating the largest Lyapunov exponent from a scalar time series is difficult when the governing equations, tangent dynamics, and full state vector

researcharxiv-cs-lg