Search: “model-releases”

Accelerated Dopant Screening in Oxide Semiconductors via Multi-Fidelity Contextual Bandits and a Three-Tier DFT Validation Funnel

arXiv:2604.10157v1 Announce Type: cross Abstract: Band gap engineering of oxide semiconductors through doping is critical for photocatalysis and optoelectronics, yet the combinatorial space of dopant

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Model Releases

ACCIDENT: A Benchmark Dataset for Vehicle Accident Detection from Traffic Surveillance Videos

DGX agent

arXiv:2604.09819v1 Announce Type: cross Abstract: We introduce ACCIDENT, a benchmark dataset for traffic accident detection in CCTV footage, designed to evaluate models in supervised (IID and OOD) and

model-releasesarxiv-cs-ai

14 Apr 2026

ACE-Bench: A Lightweight Benchmark for Evaluating Azure SDK Usage Correctness

arXiv:2604.09564v1 Announce Type: cross Abstract: We present ACE-Bench (Azure SDK Coding Evaluation Benchmark), an execution-free benchmark that provides fast, reproducible pass or fail signals for wh

ActorMind: Emulating Human Actor Reasoning for Speech Role-Playing

arXiv:2604.11103v1 Announce Type: cross Abstract: Role-playing has garnered rising attention as it provides a strong foundation for human-machine interaction and facilitates sociological research. How

Adapting 2D Multi-Modal Large Language Model for 3D CT Image Analysis

arXiv:2604.10233v1 Announce Type: cross Abstract: 3D medical image analysis is of great importance in disease diagnosis and treatment. Recently, multimodal large language models (MLLMs) have exhibited

AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation

arXiv:2604.09617v1 Announce Type: new Abstract: Transparent and standardized documentation is essential for building trustworthy generative AI (GAI) systems. However, existing automated methods for ge

ADD for Multi-Bit Image Watermarking

arXiv:2604.11491v1 Announce Type: cross Abstract: As generative models enable rapid creation of high-fidelity images, societal concerns about misinformation and authenticity have intensified. A promis

Advancing Polish Language Modeling through Tokenizer Optimization in the Bielik v3 7B and 11B Series

arXiv:2604.10799v1 Announce Type: cross Abstract: The development of the Bielik v3 PL series, encompassing both the 7B and 11B parameter variants, represents a significant milestone in the field of la

AffordSim: A Scalable Data Generator and Benchmark for Affordance-Aware Robotic Manipulation

arXiv:2604.11674v1 Announce Type: cross Abstract: Simulation-based data generation has become a dominant paradigm for training robotic manipulation policies, yet existing platforms do not incorporate

AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts

arXiv:2601.11044v3 Announce Type: replace Abstract: Large Language Models (LLMs) based autonomous agents demonstrate multifaceted capabilities to contribute substantially to economic production. Howev

Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning

arXiv:2601.03641v4 Announce Type: replace Abstract: Large Language Model (LLM)-based agents significantly extend the utility of LLMs by interacting with dynamic environments. However, enabling agents

Agent Mentor: Framing Agent Knowledge through Semantic Trajectory Analysis

arXiv:2604.10513v1 Announce Type: new Abstract: AI agent development relies heavily on natural language prompting to define agents' tasks, knowledge, and goals. These prompts are interpreted by Large

Agent^2 RL-Bench: Can LLM Agents Engineer Agentic RL Post-Training?

arXiv:2604.10547v1 Announce Type: new Abstract: We introduce Agent^2 RL-Bench, a benchmark for evaluating agentic RL post-training -- whether LLM agents can autonomously design, implement, and run com

Agentic Aggregation for Parallel Scaling of Long-Horizon Agentic Tasks

arXiv:2604.11753v1 Announce Type: new Abstract: We study parallel test-time scaling for long-horizon agentic tasks such as agentic search and deep research, where multiple rollouts are generated in pa

Agentic Application in Power Grid Static Analysis: Automatic Code Generation and Error Correction

arXiv:2604.09995v1 Announce Type: cross Abstract: This paper introduces an LLM agent that automates power grid static analysis by converting natural language into MATPOWER scripts. The framework utili

Agentic Exploration of PDE Spaces using Latent Foundation Models for Parameterized Simulations

arXiv:2604.09584v1 Announce Type: new Abstract: Flow physics and more broadly physical phenomena governed by partial differential equations (PDEs), are inherently continuous, high-dimensional and ofte

Agri-R1: Agricultural Reasoning for Disease Diagnosis via Automated-Synthesis and Reinforcement Learning

arXiv:2601.04672v2 Announce Type: replace-cross Abstract: Agricultural disease diagnosis challenges VLMs, as conventional fine-tuning requires extensive labels, lacks interpretability, and generalizes

AI-enhanced tuning of quantum dot Hamiltonians toward Majorana modes

arXiv:2601.02149v3 Announce Type: replace-cross Abstract: We propose a neural network-based model capable of learning the broad landscape of working regimes in quantum dot simulators, and using this k

AIM-Bench: Benchmarking and Improving Affective Image Manipulation via Fine-Grained Hierarchical Control

arXiv:2604.10454v1 Announce Type: new Abstract: Affective Image Manipulation (AIM) aims to evoke specific emotions through targeted editing. Current image editing benchmarks primarily focus on object-

AIM: Intent-Aware Unified world action Modeling with Spatial Value Maps

arXiv:2604.11135v1 Announce Type: cross Abstract: Pretrained video generation models provide strong priors for robot control, but existing unified world action models still struggle to decode reliable

AIMER: Calibration-Free Task-Agnostic MoE Pruning

arXiv:2603.18492v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) language models increase parameter capacity without proportional per-token compute, but the deployment still requires stori

Aligning What LLMs Do and Say: Towards Self-Consistent Explanations

arXiv:2506.07523v3 Announce Type: replace Abstract: Large language models (LLMs) seem to offer an easy path to interpretability: just ask them to explain their answers. Yet the features driving an ans

AmodalSVG: Amodal Image Vectorization via Semantic Layer Peeling

arXiv:2604.10940v1 Announce Type: new Abstract: We introduce AmodalSVG, a new framework for amodal image vectorization that produces semantically organized and geometrically complete SVG representatio

Anthropic recently changed Claude Enterprise pricing; customers now pay $20/month per user plus consumption-based charges, instead of a fixed subscription (The Information)

The Information: Anthropic recently changed Claude Enterprise pricing; customers now pay $20/month per user plus consumption-based charges, instead of a fixed subscription — Businesses whose employees

model-releasestechmeme

Anthropic redesigns Claude Code on desktop, adding a sidebar for managing multiple sessions, a drag-and-drop layout, an integrated terminal, and a file editor (Claude)

Claude: Anthropic redesigns Claude Code on desktop, adding a sidebar for managing multiple sessions, a drag-and-drop layout, an integrated terminal, and a file editor — Today, we're releasing a redesi

model-releasestechmeme

AnySlot: Goal-Conditioned Vision-Language-Action Policies for Zero-Shot Slot-Level Placement

model-releasesarxiv-cs-ro

arXiv:2604.10432v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies have emerged as a versatile paradigm for generalist robotic manipulation. However, precise object placement under

AOP-Smart: A RAG-Enhanced Large Language Model Framework for Adverse Outcome Pathway Analysis

arXiv:2604.10874v1 Announce Type: cross Abstract: Adverse Outcome Pathways (AOPs) are an important knowledge framework in toxicological research and risk assessment. In recent years, large language mo

Architecture-Agnostic Modality-Isolated Gated Fusion for Robust Multi-Modal Prostate MRI Segmentation

arXiv:2604.10702v1 Announce Type: cross Abstract: Multi-parametric prostate MRI -- combining T2-weighted, apparent diffusion coefficient, and high b-value diffusion-weighted sequences -- is central to

Are We Recognizing the Jaguar or Its Background? A Diagnostic Framework for Jaguar Re-Identification

arXiv:2604.09690v1 Announce Type: new Abstract: Jaguar re-identification (re-ID) from citizen-science imagery can look strong on standard retrieval metrics while still relying on the wrong evidence, s

Assessing the Pedagogical Readiness of Large Language Models as AI Tutors in Low-Resource Contexts: A Case Study of Nepal's K-10 Curriculum

arXiv:2604.09619v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into educational ecosystems promises to democratize access to personalized tutoring, yet the readiness

ATANT v1.1: Positioning Continuity Evaluation Against Memory, Long-Context, and Agentic-Memory Benchmarks

arXiv:2604.10981v1 Announce Type: new Abstract: ATANT v1.0 (arXiv:2604.06710) defined continuity as a system property with 7 required properties and introduced a 10-checkpoint, LLM-free evaluation met

AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruption

arXiv:2508.03793v2 Announce Type: replace Abstract: Long-context large language models (LLMs), such as Gemini-2.5-Pro and Claude-Sonnet-4, are increasingly used to empower advanced AI systems, includi

Audio Flamingo Next: Next-Generation Open Audio-Language Models for Speech, Sound, and Music

arXiv:2604.10905v1 Announce Type: cross Abstract: We present Audio Flamingo Next (AF-Next), the next-generation and most capable large audio-language model in the Audio Flamingo series, designed to ad

Audio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing

arXiv:2604.10708v1 Announce Type: cross Abstract: Recent progress in multimodal models has spurred rapid advances in audio understanding, generation, and editing. However, these capabilities are typic

AutoMS: Multi-Agent Evolutionary Search for Cross-Physics Inverse Microstructure Design

arXiv:2603.27195v2 Announce Type: replace Abstract: Designing microstructures with coupled cross-physics objectives is a fundamental challenge where traditional topology optimization is often computat

AWS launches Amazon Bio Discovery, an AI-powered application designed to speed up drug development, giving scientists access to biological foundation models (Reuters)

Reuters: AWS launches Amazon Bio Discovery, an AI-powered application designed to speed up drug development, giving scientists access to biological foundation models — Amazon's (AMZN.O) cloud unit on

model-releasestechmeme

Back to the Barn with LLAMAs: Evolving Pretrained LLM Backbones in Finetuning Vision Language Models

arXiv:2604.10985v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have rapidly advanced by leveraging powerful pre-trained Large Language Models (LLMs) as core reasoning backbones. As new

BadGraph: A Backdoor Attack Against Latent Diffusion Model for Text-Guided Graph Generation

arXiv:2510.20792v4 Announce Type: replace-cross Abstract: The rapid progress of graph generation has raised new security concerns, particularly regarding backdoor vulnerabilities. While prior work has

BankerToolBench: Evaluating AI Agents in End-to-End Investment Banking Workflows

arXiv:2604.11304v1 Announce Type: new Abstract: Existing AI benchmarks lack the fidelity to assess economically meaningful progress on professional workflows. To evaluate frontier AI agents in a high-

BareBones: Benchmarking Zero-Shot Geometric Comprehension in VLMs

arXiv:2604.10528v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) demonstrate remarkable zero-shot recognition capabilities across a diverse spectrum of multimodal tasks, it yet rema

Beginner guide for anyone coming from ChatGPT who has never touched Claude before. No terminal, no tech talk. Ten steps, each with a plain explanation and a tip.

This Reddit post from r/ChatGPT is a non-technical beginner's guide designed to help users transition from ChatGPT to Claude, structured as ten plain-language steps with practical tips — requiring no

model-releasesr-chatgpt

Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation

arXiv:2504.14988v3 Announce Type: replace Abstract: Recent advancements in Large Vision-Language Models (LVLMs) have demonstrated remarkable multimodal perception capabilities, garnering significant a

Benchmarking Vision-Language Models under Contradictory Virtual Content Attacks in Augmented Reality

arXiv:2604.05510v2 Announce Type: replace Abstract: Augmented reality (AR) has rapidly expanded over the past decade. As AR becomes increasingly integrated into daily life, its security and reliabilit

Beyond Matching to Tiles: Bridging Unaligned Aerial and Satellite Views for Vision-Only UAV Navigation

arXiv:2603.22153v3 Announce Type: replace-cross Abstract: Recent advances in cross-view geo-localization (CVGL) methods have shown strong potential for supporting unmanned aerial vehicle (UAV) navigat

Beyond Statistical Co-occurrence: Unlocking Intrinsic Semantics for Tabular Data Clustering

arXiv:2604.10865v1 Announce Type: new Abstract: Deep Clustering (DC) has emerged as a powerful tool for tabular data analysis in real-world domains like finance and healthcare. However, most existing

Beyond the Beep: Scalable Collision Anticipation and Real-Time Explainability with BADAS-2.0

arXiv:2604.05767v2 Announce Type: replace-cross Abstract: We present BADAS-2.0, the second generation of our collision anticipation system, building on BADAS-1.0, which showed that fine-tuning V-JEPA2

Bias Detection in Emergency Psychiatry: Linking Negative Language to Diagnostic Disparities

arXiv:2509.02651v3 Announce Type: replace-cross Abstract: The emergency department (ED) is a high stress environment with increased risk of clinician bias exposure. In the United States, Black patient

BiCLIP: Domain Canonicalization via Structured Geometric Transformation

arXiv:2603.08942v2 Announce Type: replace-cross Abstract: Recent advances in vision-language models (VLMs) have demonstrated remarkable zero-shot capabilities, yet adapting these models to specialized