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BranPO: Scalable Contrastive Branch Sampling for Long-Horizon Agentic Reinforcement Learning

arXiv:2602.03719v2 Announce Type: replace Abstract: Agentic reinforcement learning enables large language models to perform multi-turn planning and tool use, but long-horizon training remains challeng

safetyarxiv-cs-cl

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Model Releases

BraveGuard: From Open-World Threats to Safer Computer-Use Agents

DGX agent

arXiv:2606.01166v1 Announce Type: cross Abstract: Computer-use agents extend language models from text generation to sustained interaction with files, terminals, browsers, and external tools. This shi

model-releasesarxiv-cs-cl

2 Jun 2026

Breaking the Information Silo: Semantic Personas for Cross-Domain Recommendation

arXiv:2606.01783v1 Announce Type: cross Abstract: Digital platforms increasingly operate as isolated information silos, limiting their ability to construct comprehensive user representations across do

Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge

arXiv:2602.02470v2 Announce Type: replace Abstract: Autoregressive large language models (LLMs) have achieved remarkable success in many complex tasks, yet they can still fail in very simple logical r

Bridging Reasoning Trajectories in On-Policy Distillation via Near-Future Guidance

arXiv:2606.00305v1 Announce Type: cross Abstract: On-Policy Distillation (OPD) improves large language model reasoning by training a student model on trajectories sampled from its own policy under tea

Bridging Requirements and Architecture: Multi-Agent Orchestration with External Knowledge and Hierarchical Memory

arXiv:2606.01385v1 Announce Type: cross Abstract: Software architecture design is a critical yet inherently complex and knowledge-intensive phase that requires balancing competing quality attributes a

Bridging the 2D-3D Gap: A Hierarchical Semantic-Geometric Map for Vision Language Navigation

arXiv:2606.00095v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables embodied agents to reach target locations in unseen environments by following language instructions. Despite

Bridging the Gap: Transfer Learning from English PLMs to Malaysian English

arXiv:2407.01374v2 Announce Type: replace Abstract: Malaysian English is a low resource creole language, where it carries the elements of Malay, Chinese, and Tamil languages, in addition to Standard E

tutorialsarxiv-cs-cl

Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions

arXiv:2509.23782v4 Announce Type: replace Abstract: While large language models (LLMs) perform strongly on diverse tasks, their trustworthiness is limited by erratic behavior that is unfaithful to the

researcharxiv-cs-cl

Bridging the Last Mile of Time Series Forecasting with LLM Agents

arXiv:2606.02497v1 Announce Type: new Abstract: Time series forecasting has advanced rapidly, especially with the emergence of foundation models that show strong zero-shot performance on numerical ext

Bridging the Sim-to-Real Gap in Semiconductor Visual Program Synthesis via Input Binarization

arXiv:2606.02434v1 Announce Type: new Abstract: Precise parametric control over circuit geometry is essential for semiconductor inspection, yet obtaining sufficient real training data remains costly.

Bridging Topology and Deep Representation Learning: A TDA-ViT Fusion Model for Four-Class Brain Tumor Classification

arXiv:2606.00927v1 Announce Type: new Abstract: Accurate brain tumor classification from magnetic resonance imaging (MRI) is a key requirement for early diagnosis and clinical decision-making. Vision

researcharxiv-cs-cv

BRo-JEPA: Learning Modular Arithmetic in Latent Space

arXiv:2606.01372v1 Announce Type: cross Abstract: Can neural networks learn abstract algebraic rules, or do they merely memorize training patterns? We investigate this using MNIST digits as states and

tutorialsarxiv-cs-ai

Hardware

BudgetDraft: Acceptance-Aware Multi-View Training for Sparse-KV Speculative Decoding

arXiv:2606.00144v1 Announce Type: cross Abstract: Speculative decoding speeds up autoregressive decoding by using a drafter to propose multiple tokens that a verifier validates in parallel. In resourc

hardwarearxiv-cs-ai

Build agents you can trust across any framework with open evals and a control standard

tutorialsmicrosoft-foundry

Learn how Microsoft helps developers build trustworthy AI agents with open evaluations, portable runtime controls, production observability, and security workflows that work across frameworks. The pos

Build and run agents at scale with Microsoft Foundry at Build 2026

Learn how Microsoft Foundry helps developers build, deploy, and operate production-ready agents with Agent Framework, Toolboxes, hosted agents, Microsoft 365 distribution, observability, and agent opt

agentsmicrosoft-foundry

Local Ai

Build on-device personal AI agents on Windows PCs with new tools from NVIDIA and Microsoft, including secure sandboxing, faster local infere…

Build on-device personal AI agents on Windows PCs with new tools from NVIDIA and Microsoft, including secure sandboxing, faster local inference, multi-GPU support, and RTX acceleration for Windows AI

local-aicomfyui--x

Building a secure auth code flow setup using AgentCore Gateway with MCP clients

This post demonstrates how to implement Open Authorization (OAuth) Code flow as an inbound authorization mechanism for MCP servers hosted on Amazon Bedrock AgentCore Gateway. By the end of this guide,

agentsaws-ml-blog

Applications

Building apps has never been easier. With Sites, Codex can turn your work, ideas, and plans into an interactive website or app your team can…

Building apps has never been easier. With Sites, Codex can turn your work, ideas, and plans into an interactive website or app your team can explore, use, and share with a URL. Rolling out to Business

applicationsopenai--x

Business Utility of Large Language Models as Exploratory Data Analysis Agents

arXiv:2606.00051v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in analytical workflows, but their suitability as exploratory data analysis (EDA) agents in busines

Byte Pair Encoding for Efficient Time Series Forecasting

arXiv:2505.14411v4 Announce Type: replace Abstract: Existing time series tokenization methods predominantly encode a constant number of samples into individual tokens. This inflexible approach can gen

researcharxiv-cs-lg

C-LEAD: Contrastive Learning for Enhanced Adversarial Defense

arXiv:2510.27249v2 Announce Type: replace Abstract: Deep neural networks (DNNs) have achieved remarkable success in computer vision tasks such as image classification, segmentation, and object detecti

tutorialsarxiv-cs-cv

Applications

c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization

arXiv:2211.14411v5 Announce Type: replace-cross Abstract: Hyperparameter optimization (HPO) is crucial for strong performance of deep learning algorithms and real-world applications often impose some

applicationsarxiv-cs-ai

CA-BED: Conversation-Aware Bayesian Experimental Design

arXiv:2606.01182v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at static reasoning tasks, yet their performance often degrades in interactive scenarios where information must be

CAFOSat: A Strongly Annotated Dataset for Infrastructure-Aware CAFO Mapping Using High-Resolution Imagery

arXiv:2606.00548v1 Announce Type: cross Abstract: Concentrated Animal Feeding Operations (CAFOs) play an important role in agricultural production but are also associated with environmental, public he

Calibrating Uncertainty for Zero-Shot Adversarial CLIP

arXiv:2512.12997v2 Announce Type: replace-cross Abstract: CLIP delivers strong zero-shot classification but remains highly vulnerable to adversarial attacks. Prior adversarial fine-tuning work primari

Tools

California Brown Pelican

California Brown Pelican, in Fort Mason, CA, USI'm at the Microsoft Build conference today, held at Fort Mason in San Francisco. There are California Brown Pelicans diving into the water directly behi

toolssimon-willison

Can AI Review Improve Paper Drafting? An Empirical Study on 20 Computer Architecture Submissions

arXiv:2606.01013v1 Announce Type: new Abstract: Research is advancing faster than ever with artificial intelligence (AI); and so are the corresponding research papers. The exploding volume of AI-gener

Can LLM Agents Sustain Long-Horizon Organizational Dynamics?

arXiv:2606.01199v1 Announce Type: new Abstract: Large language agents are increasingly used for social simulation, yet it remains unclear whether they can sustain coherent behavior in structured organ

agentsarxiv-cs-ai

Can LLMs Reason Structurally? Benchmarking via the Lens of Data Structures

arXiv:2505.24069v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are deployed on increasingly complex tasks that require multi-step decision-making. Understanding their algorithm

Can Predicted Dynamics Exist in the Physical World?

arXiv:2606.00089v1 Announce Type: cross Abstract: Predictive Physical AI systems output state rollouts, action chunks, and latent plans, yet a low root-mean-square error (RMSE) does not imply that a p

Can Vision Language Models Learn Intuitive Physics from Interaction?

arXiv:2602.06033v2 Announce Type: replace Abstract: Pre-trained vision language models do not have good intuitions about the physical world. Recent work has shown that supervised fine-tuning can impro

tutorialsarxiv-cs-lg

Can we design legal agent verifiers that are up to 1,000x cheaper? Verifiers are LLM judges that check an agent’s work against rubric criter…

model-releasesharrison-chase--x

Can we design legal agent verifiers that are up to 1,000x cheaper? Verifiers are LLM judges that check an agent’s work against rubric criteria: they're used both in agent benchmarking and as reward si

Industry

Can we yet admit that the whole George Floyd thing was irrational national hysteria? You can still see it as poor policing, but we now know …

Can we yet admit that the whole George Floyd thing was irrational national hysteria? You can still see it as poor policing, but we now know the guy was a career criminal on a cocktail of potentially l

industryelon-musk--x

CANARY: Zero-Label Detection of Fine-Tuning Contamination in Language Models

arXiv:2606.01695v1 Announce Type: new Abstract: Adversaries can implant latent harmful behavior by poisoning as few as 1% of fine-tuning examples. The contamination is invisible to every output-level

researcharxiv-cs-lg

CanonCGT: Reference-Based Color Grading via Canonical Pivot Representation

arXiv:2606.01638v1 Announce Type: new Abstract: Reference-based color grading aims to reproduce the tonal mood and lighting of a reference while preserving color harmony and scene structure. Existing

safetyarxiv-cs-cv

Canonicalized Stable-List Replay for Private Federated Continual Learning over Language-Model Embeddings

arXiv:2606.00426v1 Announce Type: new Abstract: Federated continual learning (FCL) lets distributed clients adapt language-model heads to evolving NLP tasks without sharing raw text. Under user-level

researcharxiv-cs-lg

Local Ai

Capability Self-Assessment: Teaching LLMs to Know Their Limits

arXiv:2606.00251v1 Announce Type: new Abstract: The ability to recognize one's own limitations and decide whether to solve a problem or delegate is fundamental for reliable intelligent systems. Yet we

local-aiarxiv-cs-ai

CAPF: Guiding Search-Agent Rollouts with Credit-Attenuated Privileged Feedback

arXiv:2606.01830v1 Announce Type: new Abstract: Recent LLM search agents use reinforcement learning with verifiable rewards (RLVR) to learn search-augmented reasoning from outcome rewards. On hard pro

Applications

CardioLens: Revealing the Clinical Reality Gap of MLLMs via Multi-Sequence Cardiac MRI Evaluations

arXiv:2606.00123v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have shown strong performance on public medical benchmarks, yet existing evaluations often remain weak proxie

applicationsarxiv-cs-ai

CARE-RL: Capability-Aware Reinforcement Learning for Mitigating Cross-Domain Conflicts

arXiv:2606.00609v1 Announce Type: cross Abstract: Reinforcement learning (RL) with verifiable rewards has achieved strong progress in reasoning-oriented LLMs, but extending it to multi-domain RL remai

CAREAgent: Clinical Agent with Structured Reasoning and Tool-Integrated for Order Generation

arXiv:2606.01094v1 Announce Type: new Abstract: Clinical order generation serves as a critical bridge between clinical decision-making and real-world practice, translating medical decisions into concr

agentsarxiv-cs-ai

CARES: Context-Aware Resolution Selector for VLMs

arXiv:2510.19496v3 Announce Type: replace-cross Abstract: Large vision-language models (VLMs) commonly process images at native or high resolution to remain effective across tasks. This inflates visua

CART: Context-Anchored Recurrent Transformer -- A Parameter-Efficient Architecture with Learned Stability

model-releasesarxiv-cs-cl

arXiv:2606.01495v1 Announce Type: cross Abstract: We present CART (Context-Anchored Recurrent Transformer), a parameter-efficient language model that reuses a single shared core block R times across d

CARTE: A Benchmark for Mapping Language Model Knowledge Across France

model-releasesarxiv-cs-cl

arXiv:2606.01995v1 Announce Type: new Abstract: We introduce CARTE 1 (Culturally Anchored Regional-Territorial Evaluation), a multiplechoice benchmark for evaluating the ability of large language mode

CAST: Non-Privileged Clipped Asymmetric Self-Teaching with Advantage Flipping for GRPO

arXiv:2606.00172v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR), especially Group Relative Policy Optimization (GRPO), has been widely used to improve reasoning i

CASTLE2026 Team WDL Technical Report

model-releasesarxiv-cs-cv

arXiv:2606.00712v1 Announce Type: new Abstract: The CASTLE Challenge @ EgoVis 2026 evaluates long-form egocentric video question answering over 600+ hours of multi-perspective recordings. Each four-ch

Catch-Only-One: Non-Transferable Examples for Model-Specific Authorization

arXiv:2510.10982v2 Announce Type: replace-cross Abstract: Recent AI regulations increasingly emphasize the need for mechanisms that preserve the utility of data for AI innovation while preventing misu