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Behavior-Consistent Deep Reinforcement Learning

arXiv:2605.21214v1 Announce Type: new Abstract: Reinforcement learning (RL) often exhibits high variance across training runs, leading to unreliable performance and posing a major challenge to deploym

Benchmarking Empirical and Learning-Based Approaches for Feedforward Steering Control in Autonomous Racing

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DGX agent

arXiv:2605.21111v1 Announce Type: new Abstract: Feedforward steering control is a key component of hierarchical control architectures for autonomous racing. The goal is to reduce steering corrections

model-releasesarxiv-cs-ro

21 May 2026

Industry

Bengaluru-based Scapia, which offers travel-focused co-branded credit cards and an app, raised 63M led by GC, a source says at a 500M+ post-money valuation (Jagmeet Singh/TechCrunch)

Jagmeet Singh / TechCrunch: Bengaluru-based Scapia, which offers travel-focused co-branded credit cards and an app, raised 63M led by GC, a source says at a 500M+ post-money valuation — Scapia, an Ind

industrytechmeme

Beyond Numerical Features: CNN-Driven Algorithm Selection via Contour Plots for Continuous Black-Box Optimization

arXiv:2605.20797v1 Announce Type: new Abstract: The present paper introduces a new representation-driven approach to per-instance algorithm selection, applied to black-box optimization, for automatica

Beyond Routing: Characterising Expert Tuning and Representation in Vision Mixture-of-Experts

arXiv:2605.20610v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models are often interpreted by analysing which categories are routed to which experts. However, routing alone does not reveal

Beyond Semantic Similarity: A Two-Phase Non-Parametric Retrieval Workflow for Corporate Credit Underwriting

arXiv:2605.20684v1 Announce Type: new Abstract: Corporate credit underwriting requires analysts to extract actionable evidence from long, heterogeneous financial documents spanning hundreds of pages a

applicationsarxiv-cs-cl

Beyond Text-to-SQL: An Agentic LLM System for Governed Enterprise Analytics APIs

arXiv:2605.21027v1 Announce Type: new Abstract: Enterprise analytics aims to make organizational data accessible for decision-making, yet non-technical users still face barriers when using traditional

safetyarxiv-cs-cl

Beyond the Bellman Recursion: A Pontryagin-Guided Framework for Non-Exponential Discounting

arXiv:2605.20996v1 Announce Type: new Abstract: Most value-based and actor--critic reinforcement learning methods rely on Bellman-style recursions, yet these recursions collapse under non-exponential

Agents

Beyond Words: Multimodal LLM Knows When to Speak

arXiv:2505.14654v2 Announce Type: replace-cross Abstract: Chatbots via large language models (LLMs) generate fluent responses but often struggle with when to speak, especially for brief, timely listen

agentsarxiv-cs-cl

Biomedical AI may be headed for a replication crisis. (This work below is not about AI-generated reports; it’s about studies of biomedicine …

Biomedical AI may be headed for a replication crisis. (This work below is not about AI-generated reports; it’s about studies of biomedicine that use ML in their methods, and how they are evaluted.) In

safetygary-marcus--x

Block-Sparse Global Attention for Efficient Multi-View Geometry Transformers

arXiv:2509.07120v2 Announce Type: replace Abstract: Efficient and accurate feed-forward multi-view reconstruction has long been an important task in computer vision. Recent transformer-based models li

Industry

Bluesky and Clemson researchers detail a novel Russian influence campaign that hijacked legitimate, influential accounts to spread pro-Kremlin propaganda (Steven Lee Myers/New York Times)

Steven Lee Myers / New York Times: Bluesky and Clemson researchers detail a novel Russian influence campaign that hijacked legitimate, influential accounts to spread pro-Kremlin propaganda — The compa

industrytechmeme

Break the context window barrier with Amazon Bedrock AgentCore

model-releasesaws-ml-blog

In this post, you will learn how to implement Recursive Language Models (RLM) using Amazon Bedrock AgentCore Code Interpreter and the Strands Agents SDK. By the end, you will know how to process docum

Bridging Language Models and Financial Analysis

arXiv:2503.22693v2 Announce Type: replace-cross Abstract: The rapid advancements in Large Language Models (LLMs) have unlocked transformative possibilities in natural language processing, particularly

applicationsarxiv-cs-cl

Bridging Structure and Language: Graph-Based Visual Reasoning for Autonomous Road Understanding

model-releasesarxiv-cs-cv

arXiv:2605.20942v1 Announce Type: new Abstract: Structured road understanding of lane geometry, topology, and traffic element relationships is foundational to safe autonomous driving. While vision-lan

Tools

btw you can move your side chats any where you like

This post likely describes a feature allowing users to relocate or organize their side conversations (chat panels or sidebars) to different positions within an interface, providing flexibility in how

toolsboris-cherny--x

Bugcrowd launches reinforcement learning environments to train AI on real software vulnerabilities

model-releasessiliconangle

Crowdsourced cybersecurity company Bugcrowd Inc. today launched Reinforcement Learning Environments, a new offering that lets frontier artificial intelligence labs train models on real vulnerable soft

Build a Coding Assistant with Weaviate MCP: RAG over Code & Docs

This guide demonstrates how to build a coding assistant using Weaviate's Model Context Protocol (MCP) integration, enabling retrieval-augmented generation (RAG) capabilities over codebases and documen

model-releasesweaviate

Build AI agents for business intelligence with Amazon Bedrock AgentCore

model-releasesaws-ml-blog

In this post, we show you how OPLOG developed three AI agents using the Strands Agents SDK, deployed them to Amazon Bedrock AgentCore, and integrated Amazon Bedrock with Anthropic’s Claude Sonnet and

Industry

Build AI-powered dashboard automation agents with NLP on Amazon Bedrock AgentCore

This solution combines the power of Amazon Bedrock AgentCore, Strands Agents, and Amazon Quick transforms to deliver a secure, scalable, and intelligent system for building and operating AI agents whi

industryaws-ml-blog

Tutorials

Build an AI-powered recruitment assistant using Amazon Bedrock

In this post, we demonstrate how to build an AI-powered recruitment assistant using Amazon Bedrock that brings efficiencies to candidate evaluation, generates personalized interview questions, and pro

tutorialsaws-ml-blog

Tutorials

Building a Custom Taxonomy of AI Skills and Tasks from the Ground Up with Job Postings

arXiv:2605.21029v1 Announce Type: new Abstract: Utilizing LLMs for automated taxonomy construction presents a clear opportunity for the comprehensive, yet efficient mapping of potentially complex doma

tutorialsarxiv-cs-cl

Building Arabic NLP from the Ground Up: Twenty Years of Lessons, Failures, and Open Problems

arXiv:2605.20786v1 Announce Type: new Abstract: This paper reflects on twenty years of building NLP resources and research infrastructure for Arabic, a language spoken by hundreds of millions yet hist

researcharxiv-cs-cl

Building Deep Graph Predictors with Graph Imitation Learning

arXiv:2601.15133v3 Announce Type: replace Abstract: Recent years have seen substantial progress in neural generation of text, images, and audio, supported by mature training pipelines and large-scale

Hardware

Building Token‑Metered AI Services on Telco AI Factories

Telcos are building sovereign AI factories based on the NVIDIA Cloud Partner reference architecture to provide secure, in-country AI infrastructure with controls and performance suited for enterprise

hardwarenvidia-developer

C^2FG: Control Classifier-Free Guidance via Score Discrepancy Analysis

arXiv:2603.08155v3 Announce Type: replace Abstract: Classifier-Free Guidance (CFG) is a cornerstone of modern conditional diffusion models, yet its reliance on the fixed or heuristic dynamic guidance

CAdam: Context-Adaptive Moment Estimation for 3D Gaussian Densification in Generative Distillation

arXiv:2605.20872v1 Announce Type: new Abstract: Adaptive densification is the engine of 3D Gaussian Splatting (3DGS). However, when transposed to the optimization-based Generative Distillation paradig

Calibration vs Decision Making: Revisiting the Reliability Paradox in Unlearned Language Models

arXiv:2605.20915v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of specific training data from a model while preserving reliable behavior on the remaining data, making

Can Conversational XAI Improve User Performance? An Experimental Study

arXiv:2605.20439v1 Announce Type: new Abstract: Explainable AI (XAI) techniques aim to provide insights into predictive models and enhance user performance, yet they often fall short of these expectat

Can liveness detection models generalise to synthetic media generation techniques they were never trained on? [D]

researchr-machinelearning

Liveness detection and synthetic media detection models often fail to generalize across unseen data and struggle with content from different models. Understanding how factors like data source diversit

Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?

arXiv:2602.06500v2 Announce Type: replace Abstract: Scaling inference methods such as Markov chain Monte Carlo to high-dimensional models remains a central challenge in Bayesian deep learning. A promi

Can Vision Models Truly Forget? Mirage: Representation-Level Certification of Visual Unlearning

arXiv:2605.20282v1 Announce Type: new Abstract: Machine unlearning in Vertical Federated Learning (VFL) has attracted growing interest, yet existing methods certify forgetting solely using output-leve

safetyarxiv-cs-cv

can’t believe people assume that success on highly verifiable problems in math (where we don’t even know how many tests were performed and h…

can’t believe people assume that success on highly verifiable problems in math (where we don’t even know how many tests were performed and how many might have failed) iautomatically generalize to ever

safetygary-marcus--x

Capability neq Interpretability: Human Interpretability of Vision Foundation Models

model-releasesarxiv-cs-cv

arXiv:2605.20337v1 Announce Type: new Abstract: How interpretable are the features of leading vision models? The question is increasingly pressing as these models move from research benchmarks into hi

CardioBench: Do Echocardiography Foundation Models Generalize Beyond the Lab?

model-releasesarxiv-cs-cv

arXiv:2510.00520v2 Announce Type: replace Abstract: Foundation models are reshaping medical imaging, yet their application in echocardiography remains limited, hindered by a heavy reliance on private

CASCADE Conformal Prediction: Uncertainty-Adaptive Prediction Intervals for Two-Stage Clinical Decision Support

arXiv:2605.20468v1 Announce Type: new Abstract: Effective medication management in Parkinson's Disease (PD) is challenging due to heterogeneous disease progression, variable patient response, and medi

Catching a Moving Subspace: Low-Rank Bandits Beyond Stationarity

arXiv:2605.20269v1 Announce Type: new Abstract: Many bandit deployments (recommendation, clinical dosing, ad targeting) share two facts prior work handles only in isolation: rewards live on a low-dime

applicationsarxiv-cs-lg

Causal Discovery from Heteroscedastic Stochastic Dynamical Systems under Imperfect Physical Models

arXiv:2602.04907v2 Announce Type: replace Abstract: Causal discovery is a data-driven paradigm for analyzing complex systems, while physics-based models, such as ordinary differential equations (ODEs)

applicationsarxiv-cs-lg

Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health

arXiv:2605.20782v1 Announce Type: new Abstract: Objective: The growing availability of large-scale observational clinical datasets and challenges in conducting randomized controlled trials have spurre

Causal Path Alignment: Anchoring the Optimization Trajectory for Controllable In-Parameter Knowledge Editing

arXiv:2506.04042v2 Announce Type: replace Abstract: Knowledge editing is pivotal for efficiently updating the parametric memory of Large Language Models (LLMs), enabling them to function as evolving a

Causal Unlearning in Collaborative Optimization: Exact and Approximate Influence Reversal under Adversarial Contributions

model-releasesarxiv-cs-lg

arXiv:2605.20341v1 Announce Type: new Abstract: Federated learning systems must support data deletion requests to comply with privacy regulations, yet retraining from scratch after each deletion is co

Checking the math behind the latest headlines from OpenAI and Anthropic, link below:

Gary Marcus examines and fact-checks recent claims made by OpenAI and Anthropic in their public announcements and media coverage. The post links to detailed analysis questioning the mathematical valid

safetygary-marcus--x

CHEM: Estimating and Understanding Hallucinations in Deep Learning for Image Processing

arXiv:2512.09806v2 Announce Type: replace Abstract: Deep learning-based methods have recently achieved significant success in image reconstruction problems. However, challenges have emerged, as these

safetyarxiv-cs-cv

CHOIR: Contact-aware 4D Hand-Object Interaction Reconstruction

arXiv:2605.20992v1 Announce Type: new Abstract: We ask whether everyday open-world monocular videos can be turned into reusable 4D interaction primitives: articulated hand motion, object shape with 6D

Choose Wisely and Privately: Proactive Client Selection for Fair and Efficient Federated Learning

arXiv:2605.20975v1 Announce Type: new Abstract: Federated Learning enables collaborative model training across decentralized data sources without data transfer. Averaging-based FL is limited by the pr

Chronicle: A Multimodal Foundation Model for Joint Language and Time Series Understanding

arXiv:2605.20268v1 Announce Type: cross Abstract: Real-world time series come with text: metadata, descriptions, news, reports. Yet time series foundation models process numerical sequences in isolati

ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning

arXiv:2605.21177v1 Announce Type: cross Abstract: This work presents extsc{ChunkFT}, a memory-efficient fine-tuning framework that reformulates full-parameter fine-tuning around a dynamically activate

CIG: Exploration via Conditional Information Gain

arXiv:2605.20878v1 Announce Type: new Abstract: Intrinsic rewards for exploration in reinforcement learning condition on different contexts: lifelong rewards score each transition against accumulated