All entries

DRIV-EX: Counterfactual Explanations for Driving LLMs

arXiv:2603.00696v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as reasoning engines in autonomous driving, yet their decision-making remains opaque. We propose

safetyarxiv-cs-cl

Dual Causal Inference: Integrating Backdoor Adjustment and Instrumental Variable Learning for Medical VQA

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Clear filters

DGX agent

arXiv:2604.20306v1 Announce Type: cross Abstract: Medical Visual Question Answering (MedVQA) aims to generate clinically reliable answers conditioned on complex medical images and questions. However,

model-releasesarxiv-cs-ai

23 Apr 2026

Dual-Cluster Memory Agent: Resolving Multi-Paradigm Ambiguity in Optimization Problem Solving

arXiv:2604.20183v1 Announce Type: new Abstract: Large Language Models (LLMs) often struggle with structural ambiguity in optimization problems, where a single problem admits multiple related but confl

agentsarxiv-cs-cl

Dubious predictions that have yet to be fulfilled have given dubious people like Sam Altman and Elon Musk extraordinary power over society. …

Dubious predictions that have yet to be fulfilled have given dubious people like Sam Altman and Elon Musk extraordinary power over society. @carissaveliz's lecture @@TEDTalks (which I was lucky enough

safetygary-marcus--x

Duluth at SemEval-2026 Task 6: DeBERTa with LLM-Augmented Data for Unmasking Political Question Evasions

model-releasesarxiv-cs-cl

arXiv:2604.20168v1 Announce Type: new Abstract: This paper presents the Duluth approach to SemEval-2026 Task 6 on CLARITY: Unmasking Political Question Evasions. We address Task 1 (clarity-level class

Local Ai

DynamicRad: Content-Adaptive Sparse Attention for Long Video Diffusion

arXiv:2604.20470v1 Announce Type: new Abstract: Leveraging the natural spatiotemporal energy decay in video diffusion offers a path to efficiency, yet relying solely on rigid static masks risks losing

local-aiarxiv-cs-cv

Early-Stage Product Line Validation Using LLMs: A Study on Semi-Formal Blueprint Analysis

arXiv:2604.20523v1 Announce Type: cross Abstract: We study whether Large Language Models (LLMs) can perform feature model analysis operations (AOs) directly on semi-formal textual blueprints, i.e., co

Earth Day at #GoogleCloudNext, I’m demoing a Sustainability Agent at the @nvidia booth. Built with @Google ADK, @googlegemma, #nemotron, Clo…

Earth Day at #GoogleCloudNext, I’m demoing a Sustainability Agent at the @nvidia booth. Built with @Google ADK, @googlegemma, #nemotron, Cloud Run, @milvusio , @LangChain & @ollama to reason across im

model-releasesollama--x

Effects of Cross-lingual Evidence in Multilingual Medical Question Answering

arXiv:2604.20531v1 Announce Type: new Abstract: This paper investigates Multilingual Medical Question Answering across high-resource (English, Spanish, French, Italian) and low-resource (Basque, Kazak

researcharxiv-cs-cl

Efficient INT8 Single-Image Super-Resolution via Deployment-Aware Quantization and Teacher-Guided Training

arXiv:2604.20291v1 Announce Type: new Abstract: Efficient single-image super-resolution (SISR) requires balancing reconstruction fidelity, model compactness, and robustness under low-bit deployment, w

applicationsarxiv-cs-cv

Efficient Multi-Cohort Inference for Long-Term Effects and Lifetime Value in A/B Testing with User Learning

arXiv:2604.20777v1 Announce Type: new Abstract: In streaming platforms churn is extremely costly, yet A/B tests are typically evaluated using outcomes observed within a limited experimental horizon. E

researcharxiv-cs-lg

Efficient Reinforcement Learning using Linear Koopman Dynamics for Nonlinear Robotic Systems

arXiv:2604.19980v1 Announce Type: new Abstract: This paper presents a model-based reinforcement learning (RL) framework for optimal closed-loop control of nonlinear robotic systems. The proposed appro

safetyarxiv-cs-ro

Tutorials

Efficient Symbolic Computations for Identifying Causal Effects

arXiv:2604.20516v1 Announce Type: cross Abstract: Determining identifiability of causal effects from observational data under latent confounding is a central challenge in causal inference. For linear

tutorialsarxiv-cs-lg

Efficient Test-Time Inference via Deterministic Exploration of Truncated Decoding Trees

arXiv:2604.20500v1 Announce Type: new Abstract: Self-consistency boosts inference-time performance by sampling multiple reasoning traces in parallel and voting. However, in constrained domains like ma

researcharxiv-cs-lg

Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language Models

arXiv:2511.06209v4 Announce Type: replace Abstract: LLMs can solve complex tasks by generating long, multi-step reasoning chains. Test-time scaling (TTS) can further improve LLM performance by samplin

Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps

arXiv:2501.07399v2 Announce Type: replace Abstract: Consistent maps are key for most autonomous mobile robots, and they often use SLAM approaches to build such maps. Loop closures via place recognitio

safetyarxiv-cs-ro

Industry

Eight months early and under budget, the Roman Telescope is ready to launch

NASA's Nancy Grace Roman Space Telescope is targeting launch as early as September 2026, ahead of the May 2027 deadline. The telescope is ready for launch ahead of schedule and under budget. Roman wil

industryars-technica

Elon Musk says Tesla plans to use Intel's 14A process technology to make chips at its Terafab project, which would make Tesla the first major customer for 14A (Reuters)

Reuters: Elon Musk says Tesla plans to use Intel's 14A process technology to make chips at its Terafab project, which would make Tesla the first major customer for 14A — Tesla (TSLA.O) CEO Elon Musk s

applicationstechmeme

embers

model-releasessam-altman--x

embers GPT-5.5, not fully saturating the TikZ unicorn test yet but getting awfully close ... (yes this is actual TikZ code, I personally find it so unbelievable that I'm putting the code below for any

EmbodiedMidtrain: Bridging the Gap between Vision-Language Models and Vision-Language-Action Models via Mid-training

arXiv:2604.20012v1 Announce Type: cross Abstract: Vision-Language-Action Models (VLAs) inherit their visual and linguistic capabilities from Vision-Language Models (VLMs), yet most VLAs are built from

Emergence Transformer: Dynamical Temporal Attention Matters

arXiv:2604.19816v1 Announce Type: new Abstract: The Transformer, a breakthrough architecture in artificial intelligence, owes its success to the attention mechanism, which utilizes long-range interact

researcharxiv-cs-ai

Energy-Based Open-Set Active Learning for Object Classification

arXiv:2604.20083v1 Announce Type: cross Abstract: Active learning (AL) has emerged as a crucial methodology for minimizing labeling costs in deep learning by selecting the most valuable samples from a

applicationsarxiv-cs-cv

Tutorials

Enhancing ASR Performance in the Medical Domain for Dravidian Languages

arXiv:2604.19797v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) for low-resource Dravidian languages like Telugu and Kannada faces significant challenges in specialized medical do

tutorialsarxiv-cs-ai

Enhancing Research Idea Generation through Combinatorial Innovation and Multi-Agent Iterative Search Strategies

arXiv:2604.20548v1 Announce Type: cross Abstract: Scientific progress depends on the continual generation of innovative re-search ideas. However, the rapid growth of scientific literature has greatly

agentsarxiv-cs-ai

Enhancing Speaker Verification with Whispered Speech via Post-Processing

arXiv:2604.20229v1 Announce Type: cross Abstract: Speaker verification is a task of confirming an individual's identity through the analysis of their voice. Whispered speech differs from phonated spee

researcharxiv-cs-ai

Enterprises are learning that the assumptions that powered the cloud era are no longer enough

The agentic AI era is forcing a fundamental redesign of enterprise infrastructure — not just in the cloud, but all the way to the on-premises data center. Regulated industries, governments and enterpr

agentssiliconangle

Enterprises are leaving major AI customer experience gains on the table

Enterprises are investing heavily in AI customer experience, but many experiments are stalling out before ever going live. The culprit is a confidence gap, according to Chris Mina (pictured), chief pr

applicationssiliconangle

Environmental Understanding Vision-Language Model for Embodied Agent

arXiv:2604.19839v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong perception and reasoning abilities for instruction-following embodied agents. However, despite these a

Epistemic Constitutionalism Or: how to avoid coherence bias

arXiv:2601.14295v3 Announce Type: replace Abstract: Large language models increasingly function as artificial reasoners: they evaluate arguments, assign credibility, and express confidence. Yet their

Epistemology gives a Future to Complementarity in Human-AI Interactions

arXiv:2601.09871v2 Announce Type: replace Abstract: Human-AI complementarity is the claim that a human supported by an AI system can outperform either alone in a decision-making process. Since its int

ESGLens: An LLM-Based RAG Framework for Interactive ESG Report Analysis and Score Prediction

arXiv:2604.19779v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reports are central to investment decision-making, yet their length, heterogeneous content, and lack of stan

researcharxiv-cs-cl

ETac: A Lightweight and Efficient Tactile Simulation Framework for Learning Dexterous Manipulation

arXiv:2604.20295v1 Announce Type: new Abstract: Tactile sensors are increasingly integrated into dexterous robotic manipulators to enhance contact perception. However, learning manipulation policies t

safetyarxiv-cs-ro

Evals ~= Environments…they’re one of the best investments a team can make for improving agents Step 0: Turn On Tracing for Agents Step 1: Po…

Evals ~= Environments…they’re one of the best investments a team can make for improving agents Step 0: Turn On Tracing for Agents Step 1: Point compute at Traces to understand agent behavior, segment

agentsharrison-chase--x

Evaluating Assurance Cases as Text-Attributed Graphs for Structure and Provenance Analysis

arXiv:2604.20577v1 Announce Type: cross Abstract: An assurance case is a structured argument document that justifies claims about a system's requirements or properties, which are supported by evidence

safetyarxiv-cs-lg

Evaluating Black-Box Vulnerabilities with Wasserstein-Constrained Data Perturbations

arXiv:2603.15867v2 Announce Type: replace Abstract: The growing use of Machine Learning (ML) tools comes with critical challenges, such as limited model explainability. We propose a global explainabil

safetyarxiv-cs-lg

Evaluating the Quality of the Quantified Uncertainty for (Re)Calibration of Data-Driven Regression Models

model-releasesarxiv-cs-lg

arXiv:2508.17761v3 Announce Type: replace Abstract: In safety-critical applications data-driven models must not only be accurate but also provide reliable uncertainty estimates. This property, commonl

Eventually LIL Regret: Almost Sure lnln T Regret for a sub-Gaussian Mixture on Unbounded Data

arXiv:2512.12325v3 Announce Type: replace Abstract: We prove that a classic sub-Gaussian mixture proposed by Robbins in a stochastic setting actually satisfies a path-wise (deterministic) regret bound

researcharxiv-cs-lg

Hardware

Every conversation I have with @dylan522p, I'm really just trying to understand the supply and demand of tokens. This is a unique episode in…

Every conversation I have with @dylan522p, I'm really just trying to understand the supply and demand of tokens. This is a unique episode in that it's entirely dedicated to talking about both sides of

hardwaredylan-patel--x

Evian: Towards Explainable Visual Instruction-tuning Data Auditing

arXiv:2604.20544v1 Announce Type: cross Abstract: The efficacy of Large Vision-Language Models (LVLMs) is critically dependent on the quality of their training data, requiring a precise balance betwee

Evidence of Layered Positional and Directional Constraints in the Voynich Manuscript: Implications for Cipher-Like Structure

model-releasesarxiv-cs-cl

arXiv:2604.19762v1 Announce Type: new Abstract: The Voynich Manuscript (VMS) exhibits a script of uncertain origin whose grapheme sequences have resisted linguistic analysis. We present a systematic a

EvoAgent: An Evolvable Agent Framework with Skill Learning and Multi-Agent Delegation

arXiv:2604.20133v1 Announce Type: new Abstract: This paper proposes EvoAgent - an evolvable large language model (LLM) agent framework that integrates structured skill learning with a hierarchical sub

agentsarxiv-cs-ai

EvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs

arXiv:2604.19761v1 Announce Type: new Abstract: Modern machine learning is still largely organized around a single recipe: choose a parameterized model family and optimize its weights. Although highly

EvolveSignal: A Large Language Model Powered Coding Agent for Discovering Traffic Signal Control Strategies

arXiv:2509.03335v3 Announce Type: replace Abstract: In traffic engineering, fixed-time traffic signal control remains widely used for its low cost, stability, and interpretability. However, its design

agentsarxiv-cs-lg

Excretion Detection in Pigsties Using Convolutional and Transformerbased Deep Neural Networks

arXiv:2412.00256v3 Announce Type: replace Abstract: Animal excretions in form of urine puddles and feces are a significant source of emissions in livestock farming. Automated detection of soiled floor

researcharxiv-cs-cv

Expert Upcycling: Shifting the Compute-Efficient Frontier of Mixture-of-Experts

arXiv:2604.19835v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become the dominant architecture for scaling large language models: frontier models routinely decouple total parameters f

Explainability in Generative Medical Diffusion Models: A Faithfulness-Based Analysis on MRI Synthesis

arXiv:2602.09781v2 Announce Type: replace-cross Abstract: This study investigates the explainability of generative diffusion models in the context of medical imaging, focusing on Magnetic resonance im

applicationsarxiv-cs-ai

Explainable AML Triage with LLMs: Evidence Retrieval and Counterfactual Checks

arXiv:2604.19755v1 Announce Type: new Abstract: Anti-money laundering (AML) transaction monitoring generates large volumes of alerts that must be rapidly triaged by investigators under strict audit an

Explainable Speech Emotion Recognition: Weighted Attribute Fairness to Model Demographic Contributions to Social Bias

arXiv:2604.19763v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) systems have growing applications in sensitive domains such as mental health and education, where biased predictions