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Anthropic announces 12 Claude plugins for the legal sector, including a 'commercial counsel' tool for reviewing vendor agreements and a bar exam study tool (Rachel Metz/Bloomberg)

Rachel Metz / Bloomberg: Anthropic announces 12 Claude plugins for the legal sector, including a “commercial counsel” tool for reviewing vendor agreements and a bar exam study tool — Anthropic PBC is

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Anthropic In Talks to Raise 30 Billion at 900 Billion Valuation (Bloomberg)

Bloomberg: Anthropic In Talks to Raise 30 Billion at 900 Billion Valuation — Anthropic PBC is in early talks with investors to raise at least $30 billion in fresh financing, according to people famili

industrytechmeme

Anthropic is in talks to acquire dev tools startup Stainless for $300m+. The deal would take out an important supplier of tech to rivals Ope…

Anthropic is in talks to acquire dev tools startup Stainless for $300m+. The deal would take out an important supplier of tech to rivals OpenAI and Google. w/ @Katie_Roof https://www.theinformation.co

agentsyohei-nakajima--x

Any2Any 3D Diffusion Models with Knowledge Transfer: A Radiotherapy Planning Study

arXiv:2605.09622v1 Announce Type: cross Abstract: Voxel-wise dose prediction is a critical yet challenging task in practical radiotherapy (RT) planning, as bespoke models trained from scratch often st

AnyDepth-DETR/-YOLO: Any-depth object detection with a single network

model-releasesarxiv-cs-cv

arXiv:2605.09407v1 Announce Type: new Abstract: Modern object detectors are static, fixed-depth networks optimized for a single operating point, requiring separate models for different deployment scen

APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation

arXiv:2605.09492v1 Announce Type: cross Abstract: Large language models (LLMs) often suffer from hallucinations due to error accumulation in autoregressive decoding, where suboptimal early token choic

tutorialsarxiv-cs-ai

APEX: Audio Prototype EXplanations for Classification Tasks

arXiv:2605.10153v1 Announce Type: cross Abstract: Explainable AI (XAI) has achieved remarkable success in image classification, yet the audio domain lacks equally mature solutions. Current methods app

researcharxiv-cs-lg

Applying Graph Analysis for Unsupervised Fast Malware Fingerprinting

arXiv:2510.12811v2 Announce Type: replace-cross Abstract: Malware proliferation is increasing at a tremendous rate, with hundreds of thousands of new samples identified daily. Manual investigation of

researcharxiv-cs-lg

AQMP: Image compression through Adaptive Quadtree Refinement and Matching Pursuit with Hyperparameter Optimization

arXiv:2605.09190v1 Announce Type: new Abstract: We present AQMP, a novel image codec combining Adaptive Quadtree Refinement with Matching Pursuit. Unlike conventional Matching Pursuit methods that ope

AR-VLA: True Autoregressive Action Expert for Vision-Language-Action Models

arXiv:2603.10126v2 Announce Type: replace-cross Abstract: We propose a standalone autoregressive (AR) Action Expert that generates actions as a continuous causal sequence while conditioning on refresh

Arcane: An Assertion Reduction Framework through Semantic Clustering and MCTS-Guided Rule Exploring

arXiv:2605.10107v1 Announce Type: new Abstract: Assertion-based Verification (ABV) is essential for ensuring that hardware designs conform to their intended specifications. However, existing automated

Architecture, Not Scale: Circuit Localization in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.08853v1 Announce Type: new Abstract: Mechanistic interpretability assumes that circuit analysis becomes harder as models scale. We challenge this assumption by showing that the attention ar

ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation

arXiv:2502.09891v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has proven effective in integrating external knowledge into large language models (LLMs) for solving ques

Are vision-language models ready to zero-shot replace supervised classification models in agriculture?

model-releasesarxiv-cs-cv

arXiv:2512.15977v3 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly proposed as general-purpose solutions for visual recognition tasks, yet their reliability for agricul

Artificial Intelligence in Number Theory: LLMs for Algorithm Generation and Ensemble Methods for Conjecture Verification

arXiv:2504.19451v3 Announce Type: cross Abstract: This paper presents two concrete applications of Artificial Intelligence to algorithmic and analytic number theory. Recent benchmarks of large languag

ASACK : Adaptive Safe Active Continual Koopman Learning for Uncertain Systems with Contractive Guarantees

arXiv:2605.09659v1 Announce Type: new Abstract: Koopman operator theory provides a powerful framework for representing nonlinear dynamics through a linear operator acting on lifted observables, enabli

safetyarxiv-cs-ro

ASIA: an Autonomous System Identification Agent

arXiv:2605.10480v1 Announce Type: new Abstract: Over the years, research in system identification has provided a rich set of methods for learning dynamical models, together with well-established theor

agentsarxiv-cs-ai

AssayBench: An Assay-Level Virtual Cell Benchmark for LLMs and Agents

arXiv:2605.10876v1 Announce Type: cross Abstract: Recent advances in machine learning and large-scale biological data collections have revived the prospect of building a virtual cell, a computational

AssemPlanner: A Multi-Agent Based Task Planning Framework for Flexible Assembly System

model-releasesarxiv-cs-ro

arXiv:2605.08831v1 Announce Type: new Abstract: In flexible assembly systems, existing task planning methods require a time-consuming configuration process by multiple experts to establish a productio

Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring

arXiv:2510.13397v3 Announce Type: replace Abstract: Dropout is common in clinical studies, with up to half of patients leaving early due to side effects or other reasons. When dropout is informative (

safetyarxiv-cs-lg

Assessing Trustworthiness of AI Training Dataset using Subjective Logic -- A Use Case on Bias

arXiv:2508.13813v2 Announce Type: replace-cross Abstract: As AI systems increasingly rely on training data, assessing dataset trustworthiness has become critical, particularly for properties like fair

Applications

Assessment of RAG and Fine-Tuning for Industrial Question-Answering-Applications

arXiv:2605.09533v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly employed in enterprise question-answering (QA) systems, requiring adaptation to domain-specific knowledg

applicationsarxiv-cs-ai

ASTRA-QA: A Benchmark for Abstract Question Answering over Documents

model-releasesarxiv-cs-cl

arXiv:2605.10168v1 Announce Type: new Abstract: Document-based question answering (QA) increasingly includes abstract questions that require synthesizing scattered information from long documents or a

AstroSplat: Physics-Based Gaussian Splatting for Rendering and Reconstruction of Small Celestial Bodies

arXiv:2603.11969v2 Announce Type: replace Abstract: Image-based surface reconstruction and characterization are crucial for missions to small celestial bodies (e.g., asteroids), as it informs mission

agentsarxiv-cs-cv

ATAAT: Adaptive Threat-Aware Adversarial Tuning Framework against Backdoor Attacks on Vision-Language-Action Models

arXiv:2605.08612v1 Announce Type: new Abstract: Addressing the escalating security vulnerabilities in Vision-Language-Action (VLA) models, this study investigates backdoor attacks targeting the visual

researcharxiv-cs-ro

AtteConDA: Attention-Based Conflict Suppression in Multi-Condition Diffusion Models and Synthetic Data Augmentation

arXiv:2605.09425v1 Announce Type: cross Abstract: Recent conditional image generation methods can improve controllability by generating images that are faithful to conditions such as sketches, human p

agentsarxiv-cs-ai

Attention-based graph neural networks: a survey

arXiv:2605.08679v1 Announce Type: cross Abstract: Graph neural networks (GNNs) aim to learn well-trained representations in a lower-dimension space for downstream tasks while preserving the topologica

tutorialsarxiv-cs-ai

Attention Drift: What Autoregressive Speculative Decoding Models Learn

arXiv:2605.09992v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference by drafting future tokens with a small model, but drafter models degrade sharply under template perturb

tutorialsarxiv-cs-ai

Attention Grounded Enhancement for Visual Document Retrieval

model-releasesarxiv-cs-cl

arXiv:2511.13415v2 Announce Type: replace-cross Abstract: Visual document retrieval requires understanding heterogeneous and multi-modal content to satisfy implicit information needs. Recent advances

Attention Itself Could Retrieve.RetrieveVGGT: Training-Free Long Context Streaming 3D Reconstruction via Query-Key Similarity Retrieval

arXiv:2605.09644v1 Announce Type: new Abstract: Visual Geometry Grounded Transformer (VGGT) advances 3D reconstruction via scalable Transformer architecture, but the quadratic complexity of global att

Attention-Mamba: A Mamba-Enhanced Multi-Scale Parallel Inference Network for Medical Image Segmentation

arXiv:2402.02286v4 Announce Type: replace-cross Abstract: U-shaped architectures have long dominated the field of medical image segmentation, while Transformers are widely employed for modeling long-r

Attention Sinks in Diffusion Transformers: A Causal Analysis

arXiv:2605.09313v1 Announce Type: new Abstract: Attention sinks -- tokens that receive disproportionate attention mass -- are assumed to be functionally important in autoregressive language models, bu

safetyarxiv-cs-cv

Attractor-Vascular Coupling Theory: Formal Grounding and Empirical Validation for AAMI-Standard Cuffless Blood Pressure Estimation from Smartphone Photoplethysmography

arXiv:2605.10871v1 Announce Type: cross Abstract: This work proposes Attractor-Vascular Coupling Theory (AVCT), a mathematical framework showing that cardiac attractor geometry encodes blood pressure

Attribution-based Explanations for Markov Decision Processes

arXiv:2605.09780v1 Announce Type: new Abstract: Attribution techniques explain the outcome of an AI model by assigning a numerical score to its inputs. So far, these techniques have mainly focused on

AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs

arXiv:2509.08031v3 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) are rapidly advancing, but evaluating them remains challenging due to inefficient and non-standardized too

Auction-Based Online Policy Adaptation for Evolving Objectives

arXiv:2604.02151v2 Announce Type: replace Abstract: We consider multi-objective reinforcement learning problems where objectives come from an identical family -- such as the class of reachability obje

safetyarxiv-cs-lg

Auditing Data Membership in Reinforcement Learning With Verifiable Rewards

arXiv:2511.14045v2 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a core training stage in recent large language models (LLMs). Its reliance on

Augmented Equivariant Mesh Networks for Anatomical Segmentation

arXiv:2605.08172v1 Announce Type: new Abstract: Anatomical mesh segmentation requires models that operate directly on irregular surface geometry while remaining robust to arbitrary patient pose and me

AUHead: Realistic Emotional Talking Head Generation via Action Units Control

model-releasesarxiv-cs-cv

arXiv:2602.09534v2 Announce Type: replace Abstract: Realistic talking-head video generation is critical for virtual avatars, film production, and interactive systems. Current methods struggle with nua

Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria

arXiv:2605.08354v1 Announce Type: new Abstract: Aligning multimodal generative models with human preferences demands reward signals that respect the compositional, multi-dimensional structure of human

Automate schema generation for intelligent document processing

In this post, we'll show you how our multi-document discovery feature solves this problem. It serves as an automated pre-processing step, analyzing unknown documents, clustering them by type, and gene

tutorialsaws-ml-blog

Automated Approach for Solving Infinite-state Polynomial Reachability Games

arXiv:2605.10169v1 Announce Type: new Abstract: Reachability games are two-player games played on a graph, where the objective of exttt{REACH} player is to reach the target set whereas the objective o

Automated conjecturing with TxGraffiti

arXiv:2409.19379v2 Announce Type: replace-cross Abstract: TxGraffiti is a data-driven, heuristic-based computer program developed to automate the process of generating conjectures across various mathe

Automated Detection of Abnormalities in Zebrafish Development

arXiv:2605.10464v1 Announce Type: new Abstract: Zebrafish embryos are a valuable model for drug discovery due to their optical transparency and genetic similarity to humans. However, current evaluatio

Automated high-frequency quantification of fish communities and biomass using computer vision

arXiv:2605.10449v1 Announce Type: new Abstract: Quantifying fish community structure is essential for understanding biodiversity and ecosystem responses in a changing environment, yet existing survey

Automated Robotic Moisture Monitoring in Agricultural Fields

arXiv:2605.09050v1 Announce Type: cross Abstract: Monitoring moisture level of land in a large-scale plantation is tedious. The main objective of this project is to use a robotic kit in collaboration

Autonomous Continual Learning for Environment Adaptation of Computer-Use Agents

arXiv:2602.10356v2 Announce Type: replace Abstract: Real-world digital environments are highly diverse and dynamic. These characteristics cause agents to frequently encounter unseen environments and d

agentsarxiv-cs-cl

Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge

arXiv:2605.10370v1 Announce Type: new Abstract: Scientific knowledge on the Web is published as passive assertions and cannot decide when to validate evidence, reconcile contradictions, or update conf