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Beyond Transcripts: Iterative Peer-Editing with Audio Unlocks High-Quality Human Summaries of Conversational Speech

arXiv:2605.17652v1 Announce Type: new Abstract: There are not enough established benchmarks for the task fo speech summarization. Creating new benchmarks demands human annotation, as LLMs could embed

safetyarxiv-cs-cl

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Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval

DGX agent

arXiv:2605.16324v1 Announce Type: new Abstract: Financial market forecasting is inherently uncertain, yet most deep learning approaches rely on point predictions that provide only single-value estimat

researcharxiv-cs-lg

19 May 2026

Bidirectional Optical sensors for Actuation Tracking (BOAT) in soft lattice systems

arXiv:2605.18482v1 Announce Type: new Abstract: The growing adoption of lattice-based structures in soft robotics creates a need for advanced sensing solutions capable of monitoring their global defor

researcharxiv-cs-ro

BIDO: A Biometric Identity Online Authentication Framework

arXiv:2605.16908v1 Announce Type: cross Abstract: Security systems demand continuous, cryptograph- ically robust identity verification without requiring subjects to carry physical tokens, smart cards,

safetyarxiv-cs-cv

Bio-Inspired Event-Based Visual Servoing for Ground Robots

arXiv:2603.23672v2 Announce Type: replace-cross Abstract: Biological sensory systems are inherently adaptive, filtering out constant stimuli and prioritizing relative changes, likely enhancing computa

agentsarxiv-cs-cv

BioArtlas: Computational Clustering of Multi-Dimensional Complexity in Bioart

arXiv:2511.19162v2 Announce Type: replace-cross Abstract: Bioart's hybrid nature spanning art, science, technology, ethics, and politics defies traditional single-axis categorization. I present BioArt

BioProAgent: Neuro-Symbolic Grounding for Constrained Scientific Planning

arXiv:2603.00876v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated significant reasoning capabilities in scientific discovery but struggle to bridge the gap to physical

Local Ai

BLAgent: Agentic RAG for File-Level Bug Localization

arXiv:2605.17965v1 Announce Type: cross Abstract: Bug localization remains a key bottleneck in downstream software maintenance tasks, including root cause analysis, triage, and automated program repai

local-aiarxiv-cs-ai

BlendedNet++: A dataset and benchmark for field-resolved aerodynamics and inverse design of blended wing body aircraft

arXiv:2512.03280v2 Announce Type: replace-cross Abstract: The conceptual design of Blended Wing Body (BWB) aircraft is often constrained by the high computational cost of resolving complex aerodynamic

Body-Grounded Perspective Formation and Conative Attunement in Artificial Agents

arXiv:2605.16728v1 Announce Type: new Abstract: This paper proposes a minimal architecture for body-grounded perspective formation in artificial agents. Extending prior work, the model introduces an i

safetyarxiv-cs-ai

BoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks

arXiv:2605.17000v1 Announce Type: cross Abstract: Optimization of LLM training and inference configurations, such as hyperparameters, data mixtures, and prompts, is critical to performance, but it is

Boundedly Rational Meta-Learning in Sequential Consumer Choice

model-releasesarxiv-cs-lg

arXiv:2605.16532v1 Announce Type: new Abstract: Many consumer decisions are repeated choices under uncertainty. Standard models capture these decisions using Bayesian learning and dynamic programming:

Brain-inspired spike-timing plasticity for reliable label-efficient event-camera vision

arXiv:2605.17686v1 Announce Type: new Abstract: Deploying event-camera object detectors is constrained by per-frame labeling requirements and GPU compute demands. This work introduces three local spik

Brain Vascular Age Prediction Using Cerebral Blood Flow Velocity and Machine Learning Algorithms

arXiv:2605.16969v1 Announce Type: new Abstract: Defining vascular age in terms of physiological function has become one focal point of the extensive studies to categorize and track chronological age.

Hardware

Breaking: Andrej Karpathy just filed his Q1 2026 13F. Here's everything you need to know about his recent 13F Top 10 positions: 1. VanEck Se…

Breaking: Andrej Karpathy just filed his Q1 2026 13F. Here's everything you need to know about his recent 13F Top 10 positions: 1. VanEck Semiconductor ETF - SMH - [Put] — 2.04B 2. Nvidia - NVDA - [Pu

hardwaredylan-patel--x

Breaking Annotation Barriers: Generalized Video Quality Assessment via Ranking-based Self-Supervision

arXiv:2505.03631v4 Announce Type: replace Abstract: Video quality assessment (VQA) is essential for quantifying perceptual quality in various video processing workflows, spanning from camera capture s

Breaking the accuracy-resource dilemma: a lightweight adaptive video inference enhancement

arXiv:2601.14568v2 Announce Type: replace-cross Abstract: Existing video inference (VI) enhancement methods typically aim to improve performance by scaling up model sizes and employing sophisticated n

Bridging Data Trials and Task Barriers: A Unified Framework for Sketch Biometric Identification

arXiv:2605.17367v1 Announce Type: new Abstract: Different from existing cross-modality identification tasks (e.g., heterogeneous face recognition, sketch re-identification, etc.), we introduce a novel

Tutorials

Bridging the Gap between Sparse Matrix Reordering and Factorization: A Deep Learning Framework for Fill-in Reduction

arXiv:2605.17339v1 Announce Type: new Abstract: Sparse matrix reordering can significantly reduce the fill-in during matrix factorization, thereby decreasing the computational and storage requirements

tutorialsarxiv-cs-lg

Bridging the Gap: Converting Read Text to Conversational Dialogue

arXiv:2605.18001v1 Announce Type: new Abstract: In recent advancements within speech processing, converting read speech to conversational speech has gained significant attention. The primary challenge

researcharxiv-cs-cl

Bridging the Intention-Expression Gap: Aligning Multi-Dimensional Preferences via Hierarchical Relevance Feedback in Text-to-Image Diffusion

arXiv:2603.14936v3 Announce Type: replace Abstract: Users often possess a clear visual intent but struggle to articulate it precisely in language. This intention-expression gap makes aligning generate

safetyarxiv-cs-cv

Bridging the Modality Bottleneck in Pathology MIL through Virtual Molecular Staining

arXiv:2605.16392v1 Announce Type: cross Abstract: Multiple instance learning (MIL) is the dominant framework for whole-slide image analysis in computational pathology, typically combining a frozen pat

researcharxiv-cs-cv

Bridging the Version Gap: Multi-version Training Improves ICD Code Prediction, Especially for Rare Codes

arXiv:2605.17755v1 Announce Type: cross Abstract: Clinical coding maps clinical documentation to standardized medical codes, an essential yet time-consuming administrative task that could benefit from

Applications

Buffer-Parameterized Machine Learning Surrogate Models for Cross-Technology Signal Integrity Analysis and Optimization

arXiv:2605.18170v1 Announce Type: cross Abstract: Signal integrity (SI) analysis in printed circuit board (PCB) interconnects faces increasing complexity due to diverse integrated circuit (IC) buffer

applicationsarxiv-cs-lg

Bug or Feature^2: Weight Drift, Activation Sparsity, and Spikes

arXiv:2605.17659v1 Announce Type: new Abstract: The design of modern neural architectures has converged through incremental empirical choices, yet the mechanisms governing their training dynamics rema

Building a self-improving agent on a context graph of human disagreement

You can build a measurably better agent from data you already have, without retraining a thing. The data is what your experienced humans do when they correct the AI. Capture... The post Building a sel

agentsarize-ai

Building Reliable Arithmetic Multipliers Under NBTI Aging and Process Variations

arXiv:2605.18444v1 Announce Type: cross Abstract: Hardware aging poses a significant challenge for integrated circuits (ICs), leading to performance degradation and eventual failure. In this work, we

safetyarxiv-cs-ai

Hardware

Bundle Adjustment in the Eager Mode

arXiv:2409.12190v4 Announce Type: replace-cross Abstract: Bundle adjustment (BA) is a critical technique in various robotic applications such as simultaneous localization and mapping (SLAM), augmented

hardwarearxiv-cs-cv

By now, you've probably heard about Gemini Omni, our new model designed to create anything from any input, starting with video. But... what'…

model-releasesgoogle-ai--x

Google AI announced Gemini Omni, a new multimodal model capable of generating diverse content types from various input formats, with initial focus on video generation capabilities. The model represent

Byzantine-Resilient Federated Learning via QUBO-Based Client Selection on Quantum Annealers

arXiv:2605.16438v1 Announce Type: cross Abstract: Federated Learning (FL) trains a global model across decentralized clients while preserving data privacy, but at scale it is vulnerable to malicious u

CAB: Accelerating Flow and Diffusion Sampling via Rectification and Corrected Adams-Bashforth

arXiv:2605.16736v1 Announce Type: new Abstract: Flow and diffusion models achieve high-fidelity, high-resolution image synthesis, but often require many function evaluations (NFEs) at sampling time. E

researcharxiv-cs-cv

CADS: Conformal Adaptive Decision System for Cost-Efficient Image Classification

arXiv:2605.16401v1 Announce Type: new Abstract: While high-capacity AI models have advanced state-of-the-art performance, their practical deployment is often hindered by high inference costs, environm

researcharxiv-cs-cv

Calibeating for general proper losses: A Bregman divergence approach

arXiv:2605.17269v1 Announce Type: new Abstract: This work introduces a general framework for calibeating based on regret minimization. As compared to Foster and Hart's seminal calibeating work which h

Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents

arXiv:2602.16699v3 Announce Type: replace-cross Abstract: LLM agents are deployed in environments where they must interact to acquire information. In these scenarios, the agent must reason about inher

agentsarxiv-cs-ai

Industry

calling it now. LangSmith Engine going to be our fastest growing product yet. https://www.langchain.com/blog/introducing-langsmith-engine

LangSmith Engine is a new product from LangChain that an executive predicts will become the company's fastest-growing offering. The announcement was made via blog post on LangChain's website and share

industrysonya-huang--x

CAM-Bench: A Benchmark for Computational and Applied Mathematics in Lean

arXiv:2605.17255v1 Announce Type: new Abstract: Formal theorem-proving benchmarks enable mechanically verifiable evaluation of mathematical reasoning in large language models. However, existing benchm

CAM-VFD: Cross-Attention Multimodal Video Forgery Detection

arXiv:2605.17133v1 Announce Type: cross Abstract: The rapid advancement of Deepfake technologies and video manipulation tools poses a critical challenge to multimedia forensics, judicial evidence inte

Applications

Can Adaptive Gradient Methods Converge under Heavy-Tailed Noise? A Case Study of AdaGrad

arXiv:2605.18694v1 Announce Type: cross Abstract: Many tasks in modern machine learning are observed to involve heavy-tailed gradient noise during the optimization process. To manage this realistic an

applicationsarxiv-cs-lg

Can Heterogeneous Language Models Be Fused?

arXiv:2604.01674v2 Announce Type: replace Abstract: Model merging aims to integrate multiple expert models into a single model that inherits their complementary strengths without incurring the inferen

Industry

Can I get my agents on the phone?

This article likely discusses the feasibility and methods of contacting AI agents or customer service representatives by phone, exploring whether voice communication is available as an interaction opt

industryben-s-bites

Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment

arXiv:2603.23638v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly tested on complex tasks, but their ability to allocate scarce resources over long horizons remain

agentsarxiv-cs-ai

Can LLMs Generate and Solve Linguistic Olympiad Puzzles?

model-releasesarxiv-cs-cl

arXiv:2509.21820v2 Announce Type: replace Abstract: In this paper, we introduce a combination of novel and exciting tasks: the solution and generation of linguistic puzzles. We focus on puzzles used i

Can LLMs Refuse Questions They Do Not Know? Measuring Knowledge-Aware Refusal in Factual Tasks

arXiv:2510.01782v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) should refuse to answer questions beyond their knowledge. This capability, which we term knowledge-aware refusal,

Can LLMs Think Like Consumers? Benchmarking Crowd-Level Reaction Reconstruction with ConsumerSimBench

arXiv:2605.17079v1 Announce Type: cross Abstract: LLMs are increasingly used as ``digital consumers'' to simulate public opinion, pre-test marketing decisions, and anticipate audience response. Howeve

Can machine learning for quantum-gas experiments be explainable?

arXiv:2605.18689v1 Announce Type: cross Abstract: Virtually all aspects of many-body atomic physics are challenging: experiments are technically demanding, datasets have become enormous, and the memor

Can These Views Be One Scene? Evaluating Multiview 3D Consistency when 3D Foundation Models Hallucinate

arXiv:2605.18754v1 Announce Type: new Abstract: Multiview 3D evaluation assumes that the images being scored are observations of one static 3D scene. This assumption can fail in NVS and sparse-view re

Canonical Regularisation of Wide Feature-Learning Neural Networks

arXiv:2605.18180v1 Announce Type: cross Abstract: Wide neural networks in the feature-learning regime drive modern deep learning, and yet they remain far less studied than their kernel-regime counterp

safetyarxiv-cs-lg

CANSURF: An ASV-View Can Dataset and Benchmark for Detection and Tracking of Surface-Level Debris

arXiv:2605.16774v1 Announce Type: cross Abstract: Surface-level marine debris remains a practical bottleneck for autonomous clean-up, where small, reflective targets (e.g., aluminum cans) must be dete