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Enabling Intrinsic Reasoning over Dense Geospatial Embeddings with DFR-Gemma

model-releasesarxiv-cs-cl

arXiv:2604.07490v1 Announce Type: new Abstract: Representation learning for geospatial and spatio-temporal data plays a critical role in enabling general-purpose geospatial intelligence. Recent geospa

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End-to-end encryption for Vercel Workflow

DGX agent

Vercel Workflow now automatically encrypts all user data end-to-end with no code changes required — workflow inputs, step arguments, return values, hook payloads, and stream data are automatically...

toolsvercel-blog

10 Apr 2026

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis

arXiv:2604.07180v1 Announce Type: cross Abstract: We propose a geometric framework for longitudinal multi-parametric MRI analysis based on patient-specific energy modelling in sequence space. Rather t

tutorialsarxiv-cs-ai

Energy-Regularized Spatial Masking: A Novel Approach to Enhancing Robustness and Interpretability in Vision Models

arXiv:2604.06893v1 Announce Type: cross Abstract: Deep convolutional neural networks achieve remarkable performance by exhaustively processing dense spatial feature maps, yet this brute-force strategy

Agents

Energy Saving for Cell-Free Massive MIMO Networks: A Multi-Agent Deep Reinforcement Learning Approach

arXiv:2604.07133v1 Announce Type: cross Abstract: This paper focuses on energy savings in downlink operation of cell-free massive MIMO (CF mMIMO) networks under dynamic traffic conditions. We propose

agentsarxiv-cs-ai

Applications

Enterprise teams can now set their default build machine

Vercel Enterprise team owners can now set a default build machine at the team level, streamlining configuration across their organization. This setting automatically applies to all newly created pr...

applicationsvercel-blog

Entropy After </Think> for reasoning model early exiting

model-releasesarxiv-cs-lg

arXiv:2509.26522v3 Announce Type: replace Abstract: Reasoning LLMs show improved performance with longer chains of thought. However, recent work has highlighted their tendency to overthink, continuing

Entropy-Gradient Grounding: Training-Free Evidence Retrieval in Vision-Language Models

arXiv:2604.08456v1 Announce Type: cross Abstract: Despite rapid progress, pretrained vision-language models still struggle when answers depend on tiny visual details or on combining clues spread acros

researcharxiv-cs-cl

Applications

Environmental, Social and Governance Sentiment Analysis on Slovene News: A Novel Dataset and Models

arXiv:2604.06826v1 Announce Type: cross Abstract: Environmental, Social, and Governance (ESG) considerations are increasingly integral to assessing corporate performance, reputation, and long-term sus

applicationsarxiv-cs-ai

EPIC BACKFIRE IN IRELAND The Irish Government sent in the MILITARY to CRUSH fuel protesters…but the Crowds EXPLODED in size. Now, huge parts…

EPIC BACKFIRE IN IRELAND The Irish Government sent in the MILITARY to CRUSH fuel protesters…but the Crowds EXPLODED in size. Now, huge parts of the country are RUNNING OUT OF FUEL. Their Globalist Reg

industryelon-musk--x

Epic corruption, endless propaganda, security force crackdowns and false flag operations, election interference by a hostile foreign dictato…

Epic corruption, endless propaganda, security force crackdowns and false flag operations, election interference by a hostile foreign dictatorship… That’s Orbán’s Hungary today and, unless America wake

safetygary-marcus--x

EPIR: An Efficient Patch Tokenization, Integration and Representation Framework for Micro-expression Recognition

arXiv:2604.08106v1 Announce Type: new Abstract: Micro-expression recognition can obtain the real emotion of the individual at the current moment. Although deep learning-based methods, especially Trans

tutorialsarxiv-cs-cv

Epistemic Robust Offline Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2604.07072v1 Announce Type: new Abstract: Offline reinforcement learning learns policies from fixed datasets without further environment interaction. A key challenge in this setting is epistemic

Equivariant Multi-agent Reinforcement Learning for Multimodal Vehicle-to-Infrastructure Systems

arXiv:2604.06914v1 Announce Type: new Abstract: In this paper, we study a vehicle-to-infrastructure (V2I) system where distributed base stations (BSs) acting as road-side units (RSUs) collect multimod

safetyarxiv-cs-lg

Err... what's going on?

I was unable to retrieve the specific Reddit post from the URL provided, and my search did not return relevant results for that thread. Reddit content is often not indexed in real time, and I canno...

industryr-chatgpt

ESOM: Efficiently Understanding Streaming Video Anomalies with Open-world Dynamic Definitions

arXiv:2604.07772v1 Announce Type: new Abstract: Open-world video anomaly detection (OWVAD) aims to detect and explain abnormal events under different anomaly definitions, which is important for applic

ETCH-X: Robustify Expressive Body Fitting to Clothed Humans with Composable Datasets

arXiv:2604.08548v1 Announce Type: new Abstract: Human body fitting, which aligns parametric body models such as SMPL to raw 3D point clouds of clothed humans, serves as a crucial first step for downst

European leaders are learning there is no point trying to appease Trump. He has an insatiable appetite for flattery no matter how transparen…

European leaders are learning there is no point trying to appease Trump. He has an insatiable appetite for flattery no matter how transparently false. Like any bully, he sees weakness as an invitation

researchyann-lecun--x

Evaluating In-Context Translation with Synchronous Context-Free Grammar Transduction

arXiv:2604.07320v1 Announce Type: cross Abstract: Low-resource languages pose a challenge for machine translation with large language models (LLMs), which require large amounts of training data. One p

Evaluating LLM-Based 0-to-1 Software Generation in End-to-End CLI Tool Scenarios

model-releasesarxiv-cs-ai

arXiv:2604.06742v1 Announce Type: cross Abstract: Large Language Models (LLMs) are driving a shift towards intent-driven development, where agents build complete software from scratch. However, existi

Evaluating LLMs for Demographic-Targeted Social Bias Detection: A Comprehensive Benchmark Study

model-releasesarxiv-cs-cl

arXiv:2510.04641v3 Announce Type: replace Abstract: Large-scale web-scraped text corpora used to train general-purpose AI models often contain harmful demographic-targeted social biases, creating a re

Evaluating Low-Light Image Enhancement Across Multiple Intensity Levels

arXiv:2511.15496v2 Announce Type: replace Abstract: Imaging in low-light environments is challenging due to reduced scene radiance, which leads to elevated sensor noise and reduced color saturation. M

Evaluating PQC KEMs, Combiners, and Cascade Encryption via Adaptive IND-CPA Testing Using Deep Learning

arXiv:2604.06942v1 Announce Type: cross Abstract: Ensuring ciphertext indistinguishability is fundamental to cryptographic security, but empirically validating this property in real implementations an

Evaluating Repository-level Software Documentation via Question Answering and Feature-Driven Development

model-releasesarxiv-cs-ai

arXiv:2604.06793v1 Announce Type: cross Abstract: Software documentation is crucial for repository comprehension. While Large Language Models (LLMs) advance documentation generation from code snippets

Evaluation as Evolution: Transforming Adversarial Diffusion into Closed-Loop Curricula for Autonomous Vehicles

arXiv:2604.07378v1 Announce Type: new Abstract: Autonomous vehicles in interactive traffic environments are often limited by the scarcity of safety-critical tail events in static datasets, which biase

safetyarxiv-cs-ro

Event-Centric World Modeling with Memory-Augmented Retrieval for Embodied Decision-Making

arXiv:2604.07392v1 Announce Type: cross Abstract: Autonomous agents operating in dynamic and safety-critical environments require decision-making frameworks that are both computationally efficient and

safetyarxiv-cs-ro

Event-Level Detection of Surgical Instrument Handovers in Videos with Interpretable Vision Models

arXiv:2604.07577v1 Announce Type: new Abstract: Reliable monitoring of surgical instrument exchanges is essential for maintaining procedural efficiency and patient safety in the operating room. Automa

safetyarxiv-cs-cv

EventWeave: A Dynamic Framework for Capturing Core and Supporting Events in Dialogue Systems

arXiv:2503.23078v3 Announce Type: replace Abstract: Large language models have improved dialogue systems, but often process conversational turns in isolation, overlooking the event structures that gui

tutorialsarxiv-cs-cl

Every single one of these ads was made by one person. That’s insane, see the thread. Six months ago, that would have been impossible to say.…

industrycristobal-valenzuela--x

Every single one of these ads was made by one person. That’s insane, see the thread. Six months ago, that would have been impossible to say. The level of craft, story, and quality is quite impressive.

Everything you need to know about “Open”AI’s claims to be working on AI “for the benefit of humanity”.

The specific X/Twitter post referenced (status ID 2042632799950352702) is not publicly accessible through search results, as X requires JavaScript and login to view individual posts. However, based...

safetygary-marcus--x

EVGeoQA: Benchmarking LLMs on Dynamic, Multi-Objective Geo-Spatial Exploration

model-releasesarxiv-cs-ai

arXiv:2604.07070v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable reasoning capabilities, their potential for purpose-driven exploration in dynamic geo-spatial

EviSnap: Faithful Evidence-Cited Explanations for Cold-Start Cross-Domain Recommendation

arXiv:2604.06172v1 Announce Type: cross Abstract: Cold-start cross-domain recommender (CDR) systems predict a user's preferences in a target domain using only their source-domain behavior, yet existin

EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering

arXiv:2603.11703v2 Announce Type: replace Abstract: We introduce EvoFlows, a variable-length protein sequence-to-sequence modeling approach designed for protein engineering. Existing protein language

EvoGymCM: Harnessing Continuous Material Stiffness for Soft Robot Co-Design

model-releasesarxiv-cs-ro

arXiv:2604.08258v1 Announce Type: new Abstract: In the automated co-design of soft robots, precisely adapting the material stiffness field to task environments is crucial for unlocking their full phys

Explainable AI to Improve Machine Learning Reliability for Industrial Cyber-Physical Systems

arXiv:2601.16074v2 Announce Type: replace Abstract: Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability criticall

safetyarxiv-cs-lg

ExplainFuzz: Explainable and Constraint-Conditioned Test Generation with Probabilistic Circuits

arXiv:2604.06559v1 Announce Type: cross Abstract: Understanding and explaining the structure of generated test inputs is essential for effective software testing and debugging. Existing approaches--in

tutorialsarxiv-cs-lg

Local Ai

Explaining Neural Networks in Preference Learning: a Post-hoc Inductive Logic Programming Approach

arXiv:2604.06838v1 Announce Type: new Abstract: In this paper, we propose using Learning from Answer Sets to approximate black-box models, such as Neural Networks (NN), in the specific case of learnin

local-aiarxiv-cs-ai

Applications

Exploring Natural Language-Based Strategies for Efficient Number Learning in Children through Reinforcement Learning

arXiv:2410.08334v2 Announce Type: replace-cross Abstract: In this paper, we build a reinforcement learning framework to study how children compose numbers using base-ten blocks. Studying numerical cog

applicationsarxiv-cs-ai

Agents

Exploring Plan Space through Conversation: An Agentic Framework for LLM-Mediated Explanations in Planning

arXiv:2603.02070v2 Announce Type: replace-cross Abstract: When automating plan generation for a real-world sequential decision problem, the goal is often not to replace the human planner, but to facil

agentsarxiv-cs-cl

Exploring Temporal Representation in Neural Processes for Multimodal Action Prediction

arXiv:2604.08418v1 Announce Type: new Abstract: Inspired by the human ability to understand and predict others, we study the applicability of Conditional Neural Processes (CNP) to the task of self-sup

tutorialsarxiv-cs-ro

Extracting Breast Cancer Phenotypes from Clinical Notes: Comparing LLMs with Classical Ontology Methods

arXiv:2604.06208v1 Announce Type: cross Abstract: A significant amount of data held in Oncology Electronic Medical Records (EMRs) is contained in unstructured provider notes -- including but not limit

Extraction of linearized models from pre-trained networks via knowledge distillation

arXiv:2604.06732v1 Announce Type: new Abstract: Recent developments in hardware, such as photonic integrated circuits and optical devices, are driving demand for research on constructing machine learn

F1 moves a step closer to fixing its 2026 hybrid problem

F1's 2026 power unit regulations introduced a true 50/50 hybrid split between the internal combustion engine and the electric motor (MGU-K), while eliminating the MGU-H entirely — a change that has...

industryars-technica

Face-D(^2)CL: Multi-Domain Synergistic Representation with Dual Continual Learning for Facial DeepFake Detection

arXiv:2604.08159v1 Announce Type: new Abstract: The rapid advancement of facial forgery techniques poses severe threats to public trust and information security, making facial DeepFake detection a cri

Face2Scene: Using Facial Degradation as an Oracle for Diffusion-Based Scene Restoration

arXiv:2603.16570v2 Announce Type: replace Abstract: Recent advances in image restoration have enabled high-fidelity recovery of faces from degraded inputs using reference-based face restoration models

tutorialsarxiv-cs-cv

Fail2Drive: Benchmarking Closed-Loop Driving Generalization

arXiv:2604.08535v1 Announce Type: cross Abstract: Generalization under distribution shift remains a central bottleneck for closed-loop autonomous driving. Although simulators like CARLA enable safe an

Faithful-First Reasoning, Planning, and Acting for Multimodal LLMs

arXiv:2511.08409v4 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) frequently suffer from unfaithfulness, generating reasoning chains that drift from visual evidence or contr

Faithful GRPO: Improving Visual Spatial Reasoning in Multimodal Language Models via Constrained Policy Optimization

arXiv:2604.08476v1 Announce Type: new Abstract: Multimodal reasoning models (MRMs) trained with reinforcement learning with verifiable rewards (RLVR) show improved accuracy on visual reasoning benchma

safetyarxiv-cs-cv