Search: “models”

Reward-Guided Semantic Evolution for Test-time Adaptive Object Detection

arXiv:2605.04531v1 Announce Type: new Abstract: Open-vocabulary object detection with vision-language models (VLMs) such as Grounding DINO suffers from performance degradation under test-time distribu

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S1-MMAlign: A Large-Scale, Multi-Disciplinary Dataset for Scientific Figure-Text Understanding

DGX agent

arXiv:2601.00264v2 Announce Type: replace Abstract: Multimodal learning has revolutionized general domain tasks, yet its application in scientific discovery is hindered by the profound semantic gap be

safetyarxiv-cs-cv

7 May 2026

Segmenting proto-halos with vision transformers

arXiv:2508.00049v2 Announce Type: cross Abstract: The formation of dark-matter halos from small cosmological perturbations generated in the early universe is a highly non-linear process typically mode

Stop Automating Peer Review Without Rigorous Evaluation

arXiv:2605.03202v1 Announce Type: new Abstract: Large language models offer a tempting solution to address the peer review crisis. This position paper argues that today's AI systems should not be used

researcharxiv-cs-ai

Superposition Is Not Necessary: A Mechanistic Interpretability Analysis of Transformer Representations for Time Series Forecasting

arXiv:2605.05151v1 Announce Type: new Abstract: Transformer architectures have been widely adopted for time series forecasting, yet whether the representational mechanisms that make them powerful in N

SWE 1.6 Fast is available in Devin for Terminal. http://devin.ai/terminal

Cognition AI announced that SWE 1.6 Fast, an upgraded version of their software engineering model, is now available for use in Devin's Terminal interface. This update likely provides faster performanc

agentscognition-ai--x

SymptomAI: Towards a Conversational AI Agent for Everyday Symptom Assessment

arXiv:2605.04012v1 Announce Type: new Abstract: Language models excel at diagnostic assessments on currated medical case-studies and vignettes, performing on par with, or better than, clinical profess

Technical highlights: CogViT Vision Encoder - Built with dual-teacher distillation: SigLIP2 for semantics, DINOv3 for texture. A two-stage r…

Technical highlights: CogViT Vision Encoder - Built with dual-teacher distillation: SigLIP2 for semantics, DINOv3 for texture. A two-stage recipe, masked modeling, then contrastive pretraining, with Q

agentszhipu-ai--x

The Implicit Curriculum: Learning Dynamics in RL with Verifiable Rewards

arXiv:2602.14872v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has been a main driver of recent breakthroughs in large reasoning models. Yet it remains a mys

Towards Generative Location Awareness for Disaster Response: A Probabilistic Cross-view Geolocalization Approach

arXiv:2512.20056v2 Announce Type: replace-cross Abstract: As Earth's climate changes, it is impacting disasters and extreme weather events across the planet. Record-breaking heat waves, drenching rain

local-aiarxiv-cs-cv

Trustworthy Federated Label Distribution Learning under Annotation Quality Disparity

arXiv:2605.04827v1 Announce Type: new Abstract: Label Distribution Learning (LDL) models supervision as an instance-wise probability distribution, enabling fine-grained learning under inherent ambigui

Understanding LoRA as Knowledge Memory: An Empirical Analysis

arXiv:2603.01097v2 Announce Type: replace Abstract: Continuous knowledge updating for pre-trained large language models (LLMs) is increasingly necessary yet remains challenging. Although inference-tim

Understanding Transformers through the Lens of Pavlovian Conditioning

arXiv:2508.08289v2 Announce Type: replace Abstract: Transformer architectures have revolutionized artificial intelligence (AI) through their attention mechanisms, yet the computational principles unde

UniMoCo: Unified Modality Completion for Robust Multi-Modal Embeddings

arXiv:2505.11815v2 Announce Type: replace Abstract: Current vision-language models have been explored for multi-modal embedding tasks like information retrieval. However, they face significant challen

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UniPCB: A Generation-Assisted Detection Framework for PCB Defect Inspection

arXiv:2605.04635v1 Announce Type: new Abstract: Printed Circuit Board (PCB) defect inspection faces two compounding challenges: scarce and imbalanced defect samples that limit model training, and insu

Validity-Calibrated Reasoning Distillation

arXiv:2605.04078v1 Announce Type: new Abstract: Reasoning distillation aims to transfer multi-step reasoning capabilities from large language models to smaller, more efficient ones. While recent metho

local-aiarxiv-cs-lg

Variance Matters: Improving Domain Adaptation via Stratified Sampling

arXiv:2512.05226v2 Announce Type: replace Abstract: Domain shift remains a key challenge in deploying machine learning models to the real world. Unsupervised domain adaptation (UDA) aims to address th

safetyarxiv-cs-lg

When Engineering Outruns Intelligence: Rethinking Instruction-Guided Navigation

arXiv:2507.20021v3 Announce Type: replace-cross Abstract: Recent ObjectNav systems credit large language models (LLMs) for sizable zero-shot gains, yet it remains unclear how much comes from language

YOTOnet: Zero-Shot Cross-Domain Fault Diagnosis via Domain-Conditioned Mixture of Experts

arXiv:2605.04528v1 Announce Type: new Abstract: Mechanical equipment forms the critical backbone of modern industrial production, yet domain shift severely limits the generalization of deep learning b

A Knowledge-Driven LLM-Based Decision-Support System for Explainable Defect Analysis and Mitigation Guidance in Laser Powder Bed Fusion

arXiv:2605.01100v1 Announce Type: new Abstract: This work presents a knowledge-driven decision-support system that integrates structured defect knowledge with LLM-based reasoning to provide explainabl

safetyarxiv-cs-ai

A Scoping Review of Deep Learning Methods for Photoplethysmography Data

arXiv:2401.12783v3 Announce Type: replace-cross Abstract: Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad

A Study of Belief Revision Postulates in Multi-Agent Systems (Extended Version)

arXiv:2605.02249v1 Announce Type: new Abstract: We investigate the belief revision problem in epistemic planning, i.e., what will be the beliefs of all agents in a multi-agent system after an agent ga

ADAPTS: Agentic Decomposition for Automated Protocol-agnostic Tracking of Symptoms

arXiv:2605.03212v1 Announce Type: cross Abstract: Modeling latent clinical constructs from unconstrained clinical interactions is a unique challenge in affective computing. We present ADAPTS (Agentic

safetyarxiv-cs-cl

AhaRobot: A Low-Cost Open-Source Bimanual Mobile Manipulator for Embodied AI

arXiv:2503.10070v2 Announce Type: replace-cross Abstract: Scaling Vision-Language-Action models for embodied manipulation demands large volumes of diverse manipulation data, yet the high cost of comme

Attribution-Guided Masking for Robust Cross-Domain Sentiment Classification

arXiv:2605.03091v1 Announce Type: new Abstract: While pre-trained Transformer models achieve high accuracy on in-domain sentiment classification, they frequently experience severe performance degradat

b9041

local-aillama-cpp-releases

llama.cpp b9041 is a release build of llama.cpp, an LLM inference library written in C/C++ . The build identifier indicates this is an intermediate development release from the ggml-org/llama.cpp proj

b9047

local-aillama-cpp-releases

b9047 is a build release of llama.cpp, an open-source C/C++ library for running large language model inference on consumer hardware. The release includes pre-compiled binaries for multiple platforms i

b9048

local-aillama-cpp-releases

B9048 is a build/release of llama.cpp, an open-source C/C++ implementation for running large language model inference. The release includes optimizations and improvements to the core llama.cpp softwar

Beyond Isolated Investor: Predicting Startup Success via Roleplay-Based Collective Agents

arXiv:2512.22608v3 Announce Type: replace Abstract: Due to the high value and high failure rates of startups, predicting their success is a critical challenge. Existing approaches typically model star

Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems

arXiv:2605.01758v1 Announce Type: new Abstract: Large multimodal model-based Multi-Agent Systems (MASs) enable collaborative complex problem solving through specialized agents. However, MASs are vulne

safetyarxiv-cs-ai

Chrome’s AI features may be hogging 4GB of your computer storage

Google Chrome may be taking up more of your storage than expected thanks to a large on-device AI model file that, in some cases, is being automatically downloaded to the browser's system folders. User

local-aithe-verge-ai

ClinicBot: A Guideline-Grounded Clinical Chatbot with Prioritized Evidence RAG and Verifiable Citations

arXiv:2605.00846v1 Announce Type: new Abstract: Clinical diagnosis requires answers that are accurate, verifiable, and explicitly grounded in official guidelines. While large language models excel at

CoFlow: Coordinated Few-Step Flow for Offline Multi-Agent Decision Making

arXiv:2605.01457v1 Announce Type: new Abstract: Generative models have emerged as a major paradigm for offline multi-agent reinforcement learning (MARL), but existing approaches require many iterative

deSEO: Physics-Aware Dataset Creation for High-Resolution Satellite Image Shadow Removal

arXiv:2605.03610v1 Announce Type: new Abstract: Shadows cast by terrain and tall structures remain a major obstacle for high-resolution satellite image analysis, degrading classification, detection, a

DGPO: Distribution Guided Policy Optimization for Fine Grained Credit Assignment

arXiv:2605.03327v1 Announce Type: new Abstract: Reinforcement learning is crucial for aligning large language models to perform complex reasoning tasks. However, current algorithms such as Group Relat

safetyarxiv-cs-lg

Disease Is a Spectral Perturbation

arXiv:2605.02949v1 Announce Type: new Abstract: We propose a novel method of understanding disease transformation from a healthy baseline with biomarker-level explainability. By modeling the biomarker

DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data

arXiv:2605.03430v1 Announce Type: new Abstract: High-dimensional tabular data lacks a natural feature order, limiting the applicability of permutation-sensitive deep learning models. We propose DynaTa

E-MIA: Exam-Style Black-Box Membership Inference Attacks against RAG Systems

arXiv:2605.00955v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) equips large language models (LLMs) with external evidence by retrieving documents at inference time, but it also

researcharxiv-cs-ai

Industry

ElevenLabs adds high-profile investors after annualized revenue tops $500M

ElevenLabs Inc., a developer of artificial intelligence models optimized for audio processing, today announced that several dozen investors have joined its latest funding round. The startup first clos

industrysiliconangle

EngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions

arXiv:2605.02289v1 Announce Type: new Abstract: Engineering problem solving is central to real-world decision-making, requiring mathematical formulations that not only represent complex problems but a

Tutorials

Enhancing Visual Question Answering with Multimodal LLMs via Chain-of-Question Guided Retrieval-Augmented Generation

arXiv:2605.03790v1 Announce Type: new Abstract: With advances in multimodal research and deep learning, Multimodal Large Language Models (MLLMs) have emerged as a powerful paradigm for a wide range of

tutorialsarxiv-cs-cv

ExaGPT: Example-Based Machine-Generated Text Detection for Human Interpretability

arXiv:2502.11336v2 Announce Type: replace Abstract: Detecting texts generated by Large Language Models (LLMs) could cause grave mistakes due to incorrect decisions, such as undermining students' acade

researcharxiv-cs-cl

Faithful Mobile GUI Agents with Guided Advantage Estimator

arXiv:2605.01208v1 Announce Type: new Abstract: Vision-language model based graphical user interface (GUI) agents have shown strong interaction capabilities. However, they often behave unfaithfully, r

Flow Matching on Symmetric Spaces

arXiv:2605.03588v1 Announce Type: new Abstract: We introduce a general framework for training flow matching models on Riemannian symmetric spaces, a large class of manifolds that includes the sphere,

From Synthesis to Clinical Assistance: A Strategy-Aware Agent Framework for Autism Intervention based on Real Clinical Dataset

arXiv:2605.02916v1 Announce Type: new Abstract: The development of AI-assisted Early Intensive Behavioral Intervention (EIBI) for Autism Spectrum Disorder (ASD) is severely constrained by data scarcit

agentsarxiv-cs-lg

GDPR Auto-Formalization with AI Agents and Human Verification

arXiv:2604.14607v2 Announce Type: replace Abstract: We study the overall process of automatic formalization of GDPR provisions using large language models, within a human-in-the-loop verification fram

Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning

arXiv:2605.02913v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a central post-training tool for improving the reasoning abilities of large language models (LLMs). In these syst

agentsarxiv-cs-lg

GhostServe: A Lightweight Checkpointing System in the Shadow for Fault-Tolerant LLM Serving

arXiv:2605.00831v1 Announce Type: cross Abstract: The rise of million-token, agent-based applications has placed unprecedented demands on large language model (LLM) inference services. The long-runnin