Search: “models”

arXiv:2604.23996v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a prevalent backbone for large vision-language models (VLMs), yet how modality-specific signals should guide expert

tutorialsarxiv-cs-cv

Surface Sensitivity in Lean 4 Autoformalization

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DGX agent

arXiv:2604.23135v1 Announce Type: new Abstract: Natural-language variation poses a key challenge in Lean autoformalization: semantically equivalent paraphrases of the same theorem statements can induc

researcharxiv-cs-lg

28 Apr 2026

Tessera: Secure, Near-Line-Rate Weight Streaming for UMA Edge Accelerators

arXiv:2604.23205v1 Announce Type: cross Abstract: Deploying proprietary Deep Neural Networks (DNNs) on commodity edge devices demands hardware-backed Digital Rights Management (DRM) capable of withsta

The Collapse of Heterogeneity in Silicon Philosophers

arXiv:2604.23575v1 Announce Type: cross Abstract: Silicon samples are increasingly used as a low-cost substitute for human panels and have been shown to reproduce aggregate human opinion with high fid

safetyarxiv-cs-cl

Thinking Like a Clinician: A Cognitive AI Agent for Clinical Diagnosis via Panoramic Profiling and Adversarial Debate

arXiv:2604.23605v1 Announce Type: new Abstract: The application of large language models (LLMs) in clinical decision support faces significant challenges of 'tunnel vision' and diagnostic hallucinatio

Applications

Toward Real-World Adoption of Portrait Relighting via Hybrid Domain Knowledge Fusion

arXiv:2604.23094v1 Announce Type: new Abstract: The real-world adoption of portrait relighting is hindered by dataset domain gaps, camera sensitivity, and computational costs. We address these challen

applicationsarxiv-cs-cv

Turtle shell clustering: A mixture approach to discriminative clustering with applications to flow cytometry and other data

arXiv:2604.23083v1 Announce Type: cross Abstract: Generative approaches to clustering provide information on geometric properties of clusters, whereas discriminative approaches provide boundaries betw

Uncertainty Quantification for LLM Function-Calling

arXiv:2604.22985v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed to autonomously solve real-world tasks. A key ingredient for this is the LLM Function-Calling par

agentsarxiv-cs-cl

Value Alignment Tax: Measuring Value Trade-offs in LLM Alignment

arXiv:2602.12134v2 Announce Type: replace Abstract: Existing work on value alignment typically characterizes value relations statically, ignoring how alignment interventions, such as prompting, fine-t

VAMP-Net: An Interpretable Multi-Path Network of Genomic Permutation-Invariant Set Attention and Quality-Aware 1D-CNN for MTB Drug Resistance

arXiv:2512.21786v2 Announce Type: replace Abstract: Genomic prediction of drug resistance in Mycobacterium tuberculosis is often hindered by complex epistatic interactions and variable sequencing qual

WeatherSeg: Weather-Robust Image Segmentation using Teacher-Student Dual Learning and Classifier-Updating Attention

arXiv:2604.22824v1 Announce Type: cross Abstract: WeatherSeg, an advanced semi-supervised segmentation framework, addresses autonomous driving's environmental perception challenges in adverse weather

What a week at @iclr_conf in Rio 🇧🇷 ! As my first conference, it would have been hard to ask for a better experience 😍. I had the chance …

What a week at @iclr_conf in Rio 🇧🇷 ! As my first conference, it would have been hard to ask for a better experience 😍. I had the chance to present two papers: - EB-JEPA https://github.com/facebookres

researchyann-lecun--x

What if I want my coding agent to mention goblins? (If you don't know the context for this, I suspect it will become viral soon enough)

This post likely discusses how to prompt or configure an AI coding agent to incorporate unexpected or whimsical elements like goblins into its outputs, possibly as part of a broader discussion about A

agentsethan-mollick--x

Why AI Harms Can't Be Fixed One Identity at a Time: What 5300 Incident Reports Reveal About Intersectionality

arXiv:2604.24519v1 Announce Type: cross Abstract: AI risk assessment is the primary tool for identifying harms caused by AI systems. These include intersectional harms, which arise from the interactio

A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies

arXiv:2604.22227v1 Announce Type: cross Abstract: Classical robot ethics is often framed around obedience, most famously through Asimov's laws. This framing is too narrow for contemporary AI systems,

A systematic review of generative AI usage for IT project management

arXiv:2604.21958v1 Announce Type: cross Abstract: This paper aims to synthesize current knowledge on generative AI in IT project management using the PRISMA methodology to provide researchers with a c

Agentic Inequality

arXiv:2510.16853v3 Announce Type: replace-cross Abstract: Autonomous AI agents capable of complex planning and action mark a shift beyond today's generative tools. As these systems enter political and

Algorithmic Feature Highlighting for Human-AI Decision-Making

arXiv:2604.22236v1 Announce Type: cross Abstract: Human decision-makers often face choices about complex cases with many potentially relevant features, but limited bandwidth to inspect and integrate a

safetyarxiv-cs-lg

An End-to-End Ukrainian RAG for Local Deployment. Optimized Hybrid Search and Lightweight Generation

arXiv:2604.22095v1 Announce Type: new Abstract: This paper presents a highly efficient Retrieval-Augmented Generation (RAG) system built specifically for Ukrainian document question answering, which a

researcharxiv-cs-cl

An Undecidability Proof for the Plan Existence Problem

arXiv:2604.22736v1 Announce Type: cross Abstract: The plan existence problem asks, given a goal in the form of a formula in modal logic, an initial epistemic state (a pointed Kripke model), and a set

Local Ai

b8944

local-aillama-cpp-releases

Release b8944 was published on April 27, 2026 , representing a recent build of the llama.cpp project. Llama.cpp provides LLM inference in C/C++ for running large language models efficiently on consume

Hardware

Beyond Land Surface Temperature: Explainable Spatial Machine Learning Reveals Urban Morphology Effects on Human-Centric Heat Stress

arXiv:2604.22433v1 Announce Type: new Abstract: Heat exposure connects the built environment and public health, directly shaping the livability and sustainability of urban areas. Understanding the spa

hardwarearxiv-cs-lg

Breaking Watermarks in the Frequency Domain: A Modulated Diffusion Attack Framework

arXiv:2604.22220v1 Announce Type: new Abstract: Digital image watermarking has advanced rapidly for copyright protection of generative AI, yet the comparatively limited progress in watermark attack te

researcharxiv-cs-cv

CognitiveTwin: Robust Multi-Modal Digital Twins for Predicting Cognitive Decline in Alzheimer's Disease

arXiv:2604.22428v1 Announce Type: new Abstract: Predicting individual cognitive decline in Alzheimer's disease (AD) is difficult due to the heterogeneity of disease progression. Reliable clinical tool

Applications

Conditional anomaly detection using soft harmonic functions: An application to clinical alerting

arXiv:2604.21956v1 Announce Type: new Abstract: Timely detection of concerning events is an important problem in clinical practice. In this paper, we consider the problem of conditional anomaly detect

applicationsarxiv-cs-lg

Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding

arXiv:2604.22335v1 Announce Type: new Abstract: Large language models (LLMs) often produce content that contradicts or overlooks information provided in the input context, a phenomenon known as faithf

safetyarxiv-cs-cl

Tutorials

Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions

arXiv:2512.20831v2 Announce Type: replace Abstract: Real-world sequential decision-making often involves parameterized action spaces that require both, decisions regarding discrete actions and decisio

tutorialsarxiv-cs-ai

Cost-Effective Communication: An Auction-based Method for Language Agent Interaction

arXiv:2511.13193v2 Announce Type: replace Abstract: Multi-agent systems (MAS) built on large language models (LLMs) often suffer from inefficient 'free-for-all' communication, leading to exponential t

CrystalX: High-accuracy Crystal Structure Analysis Using Deep Learning

arXiv:2410.13713v2 Announce Type: replace Abstract: Atomic structure analysis of crystalline materials is a paramount endeavor in both chemical and material sciences. This sophisticated technique nece

Dynamic Coupling and Indirect Control of Jointed Robots Rolling Atop A Moving Platform

arXiv:2604.22104v1 Announce Type: new Abstract: An asymmetric two-link robot supported atop a flat platform by wheels that roll and pivot freely, but do not slip laterally, will develop forward moment

researcharxiv-cs-ro

Ethics Testing: Proactive Identification of Generative AI System Harms

arXiv:2604.22089v1 Announce Type: cross Abstract: Generative Artificial Intelligence (GAI) systems that can automatically generate content in the form of source code or other contents (e.g., images) h

Evaluating LLM-Based Goal Extraction in Requirements Engineering: Prompting Strategies and Their Limitations

arXiv:2604.22207v1 Announce Type: cross Abstract: Due to the textual and repetitive nature of many Requirements Engineering (RE) artefacts, Large Language Models (LLMs) have proven useful to automate

Explanation of Dynamic Physical Field Predictions using WassersteinGrad: Application to Autoregressive Weather Forecasting

arXiv:2604.22580v1 Announce Type: cross Abstract: As the demand to integrate Artificial Intelligence into high-stakes environments continues to grow, explaining the reasoning behind neural-network pre

Industry

Google employees ask Sundar Pichai to say no to classified military AI use

Over 600 Google employees signed a letter to CEO Sundar Pichai demanding that Google block the Pentagon from using its AI models for classified purposes, reports the The Washington Post. Its organizer

industrythe-verge-ai

How Vulnerable Is My Learned Policy? Universal Adversarial Perturbation Attacks On Modern Behavior Cloning Policies

arXiv:2502.03698v4 Announce Type: replace Abstract: Learning from demonstrations is a popular approach to train AI models; however, their vulnerability to adversarial attacks remains underexplored. We

safetyarxiv-cs-lg

Improving Driver Drowsiness Detection via Personalized EAR/MAR Thresholds and CNN-Based Classification

arXiv:2604.22479v1 Announce Type: new Abstract: Driver drowsiness is a major cause of traffic accidents worldwide, posing a serious threat to public safety. Vision-based driver monitoring systems ofte

safetyarxiv-cs-cv

Local Ai

Insect-inspired modular architectures as inductive biases for reinforcement learning

arXiv:2604.22081v1 Announce Type: new Abstract: Most reinforcement-learning (RL) controllers used in continuous control are architecturally centralized: observations are compressed into a single laten

local-aiarxiv-cs-lg

Inter-Stance: A Dyadic Multimodal Corpus for Conversational Stance Analysis

arXiv:2604.22739v1 Announce Type: new Abstract: Social interactions dominate our perceptions of the world and shape our daily behavior by attaching social meaning to acts as simple and spontaneous as

researcharxiv-cs-cv

Local Ai

K80 Tesla card

The NVIDIA Tesla K80 is a legacy GPU that can run modern LLMs through Ollama with community-maintained patches, since official Ollama dropped support for CUDA Compute Capability 3.7 hardware. Each K80

local-air-ollama

Learning Evidence Highlighting for Frozen LLMs

arXiv:2604.22565v1 Announce Type: cross Abstract: Large Language Models (LLMs) can reason well, yet often miss decisive evidence when it is buried in long, noisy contexts. We introduce HiLight, an Evi

Lifting Unlabeled Internet-level Data for 3D Scene Understanding

arXiv:2604.01907v2 Announce Type: replace-cross Abstract: Annotated 3D scene data is scarce and expensive to acquire, while abundant unlabeled videos are readily available on the internet. In this pap

Applications

Manifold Learning for Personalized and Label-Free Detection of Cardiac Arrhythmias

arXiv:2506.16494v3 Announce Type: replace Abstract: Electrocardiograms (ECGs) provide non-invasive measurements of heart activity and are established tools for detecting cardiac arrhythmias. Although

applicationsarxiv-cs-lg

Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems

arXiv:2604.22005v1 Announce Type: cross Abstract: Accurate yet low-latency channel state information (CSI) acquisition is essential for multiple-input multiple-output (MIMO) communication systems. Whi

On Star Price's new @hitpausepod podcast, ControlAI's US Director Connor Leahy (@NPCollapse) explains how AIs can already tell when they're …

On Star Price's new @hitpausepod podcast, ControlAI's US Director Connor Leahy (@NPCollapse) explains how AIs can already tell when they're being tested. Currently, we can still catch them cheating, b

safetyconnor-leahy--x

Safety and innovation are not mutually exclusive: for many companies, especially in high-trust industries, AI’s risks are also a hindrance t…

Safety and innovation are not mutually exclusive: for many companies, especially in high-trust industries, AI’s risks are also a hindrance to adoption. In this op-ed in the @FT, I underscore that Euro

safetyyoshua-bengio--x

Selective Contrastive Learning For Gloss Free Sign Language Translation

arXiv:2604.22374v1 Announce Type: new Abstract: Sign language translation (SLT) converts continuous sign videos into spoken-language text, yet it remains challenging due to the intrinsic modality mism

safetyarxiv-cs-cl

SOLAR-RL: Semi-Online Long-horizon Assignment Reinforcement Learning

arXiv:2604.22558v1 Announce Type: cross Abstract: As Multimodal Large Language Models (MLLMs) mature, GUI agents are evolving from static interactions to complex navigation. While Reinforcement Learni

SS3D: End2End Self-Supervised 3D from Web Videos

arXiv:2604.22686v1 Announce Type: new Abstract: We present SS3D, a web-scale SfM-based self-supervision pretraining pipeline for feed-forward 3D estimation from monocular video. Our model jointly pred

researcharxiv-cs-cv