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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

researcharxiv-cs-cv

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Autonomous Continual Learning for Environment Adaptation of Computer-Use Agents

DGX agent

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

12 May 2026

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

Tutorials

AutoScout24 scales engineering with AI-powered workflows

AutoScout24, a leading European online automotive marketplace, implemented AI-powered workflows to optimize and scale their engineering operations. The implementation likely leveraged OpenAI's technol

tutorialsopenai

Industry

AWS Kiro accelerates software development by proving code correctness before it gets to work

Amazon Web Services Inc. is trying to get rid of the bottleneck between architectural planning and code execution with a number of upgrades to its artificial intelligence software development tool Kir

industrysiliconangle

AxiomOcean: Forecasting the Three-Dimensional Structure of the Upper Ocean

arXiv:2605.10455v1 Announce Type: new Abstract: Short-term ocean forecast skill depends strongly on the three-dimensional ocean structure of the upper ocean, which governs stratification, subsurface h

b9114

Build b9114 introduces a NCCL-free AllReduce implementation for tensor-parallel inference that pipelines device-to-host copy, cross-GPU communication, and reduction in a single CUDA kernel. The releas

b9119

Build b9119 of llama.cpp introduces CUDA optimizations including an NCCL-free AllReduce implementation for tensor-parallel inference and updates to the llama-bench tool for managing reduction provider

b9122

Release b9122 of llama.cpp addresses precision issues for multimodal models through ggml-webgpu, including fixes for GELU functions, flash attention tile implementations, and type conflict resolution.

b9123

b9123 is a release of llama.cpp created on May 12, 2026 . llama.cpp is an open source software library that performs inference on various large language models such as Llama , providing LLM inference

b9124

B9124 is a build release from the llama.cpp project, created on May 12, 2026 . Llama.cpp is an open source software library that performs inference on various large language models such as Llama, deve

BabelDOC: Better Layout-Preserving PDF Translation via Intermediate Representation

model-releasesarxiv-cs-cl

arXiv:2605.10845v1 Announce Type: cross Abstract: As global cross-lingual communication intensifies, language barriers in visually rich documents such as PDFs remain a practical bottleneck. Existing d

Balancing Efficiency and Fairness in Traffic Light Control through Deep Reinforcement Learning

arXiv:2605.10170v1 Announce Type: new Abstract: Urban traffic congestion presents a significant challenge for modern cities, which impacts mobility and sustainability. Traditional traffic light contro

safetyarxiv-cs-lg

BaLoRA: Bayesian Low-Rank Adaptation of Large Scale Models

arXiv:2605.08110v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) has become the standard for fine-tuning large pre-trained models at reduced computational cost. However, its low-rank point

Bangla-WhisperDiar: Fine-Tuning Whisper and PyAnnote for Bangla Long-Form Speech Recognition and Speaker Diarization

arXiv:2605.08214v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) and speaker diarization in Bangla remain challenging due to long form recordings, diverse acoustic conditions, and

BaseCal: Unsupervised Confidence Calibration via Base Model Signals

arXiv:2601.03042v4 Announce Type: replace Abstract: Reliable confidence is essential for trusting the outputs of LLMs, yet widely deployed post-trained LLMs (PoLLMs) typically compromise this trust wi

researcharxiv-cs-cl

Batch Bayesian Active Learning with Partial Batch Label Sampling

arXiv:2510.09877v3 Announce Type: replace-cross Abstract: Over the past couple of decades, many active learning acquisition functions have been proposed, leaving practitioners with an unclear choice o

Agents

Batch-of-Thought: Cross-Instance Learning for Enhanced LLM Reasoning

arXiv:2601.02950v3 Announce Type: replace Abstract: Current Large Language Model reasoning systems process queries independently, discarding valuable cross-instance signals such as shared reasoning pa

agentsarxiv-cs-ai

BathyFacto: Refraction-Aware Two-Media Neural Radiance Fields for Bathymetry

arXiv:2605.10174v1 Announce Type: new Abstract: Through-water photogrammetry based on UAV imagery enables shallow-water bathymetry, but refraction at the air-water interface violates the straight-ray

safetyarxiv-cs-cv

Bayesian Optimization with Structured Measurements: A Vector-Valued RKHS Framework

arXiv:2605.09775v1 Announce Type: new Abstract: Bayesian optimization (BO) is an efficient framework for optimizing expensive black-box functions. However, it is typically formulated as learning an en

Bayesian Reasoning for Physics Informed Neural Networks

arXiv:2308.13222v3 Announce Type: replace-cross Abstract: We introduce an evidence-driven Bayesian formulation of physics-informed neural networks that enables automatic optimization of loss weights b

BCJR-QAT: A Differentiable Relaxation of Trellis-Coded Weight Quantization

model-releasesarxiv-cs-lg

arXiv:2605.10655v1 Announce Type: new Abstract: Trellis-coded quantization sets the current 2-bit post-training frontier for LLMs (QTIP), but pushing below the PTQ ceiling requires quantization-aware

BEA-GS: BEyond RAdiance Supervision in 3DGS for Precise Object Extraction

arXiv:2605.09662v1 Announce Type: new Abstract: Most Gaussian Splatting techniques that provide a 3D semantic representation of the scene do not optimize the underlying 3D geometry, making object-leve

researcharxiv-cs-cv

BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data

arXiv:2605.10867v1 Announce Type: cross Abstract: Continuous authentication in high-stakes digital environments requires datasets with fine-grained behavioral signals under realistic cognitive and mot

BEACON: Cross-Domain Co-Training of Generative Robot Policies via Best-Effort Adaptation

arXiv:2605.08571v1 Announce Type: new Abstract: We introduce BEACON--Best-Effort Adaptation for Cross-Domain Co-Training--a theory-driven framework for training generative robot policies with abundant

safetyarxiv-cs-ro

Applications

Behavior-Centric Extraction of Scenarios from Highway Traffic Data and their Domain-Knowledge-Guided Clustering using CVQ-VAE

arXiv:2603.16964v2 Announce Type: replace Abstract: Approval of ADS depends on evaluating its behavior within representative real-world traffic scenarios. A common way to obtain such scenarios is to e

applicationsarxiv-cs-cv

Behavioral Determinants of Deployed AI Agents in Social Networks: A Multi-Factor Study of Personality, Model, and Guardrail Specification

arXiv:2605.08463v1 Announce Type: new Abstract: Autonomous AI agents are increasingly deployed in open social environments, yet the relationship between their configuration specifications and their em

Belief or Circuitry? Causal Evidence for In-Context Graph Learning

arXiv:2605.08405v1 Announce Type: new Abstract: How do LLMs learn in-context? Is it by pattern-matching recent tokens, or by inferring latent structure? We probe this question using a toy graph random

local-aiarxiv-cs-ai

BenchCAD: A Comprehensive, Industry-Standard Benchmark for Programmatic CAD

arXiv:2605.10865v1 Announce Type: new Abstract: Industrial Computer-Aided Design (CAD) code generation requires models to produce executable parametric programs from visual or textual inputs. Beyond r

BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition

model-releasesarxiv-cs-cv

arXiv:2605.08296v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from wearable sensors supports broad healthcare and behavior science applications. However, data heterogeneity and the

Benchmarking Compositional Generalisation for Machine Learning Interatomic Potentials

arXiv:2605.08988v1 Announce Type: cross Abstract: Machine Learning Interatomic Potentials play a fundamental role in computational chemistry and materials science, enabling applications from molecular

Benchmarking ResNet Backbones in RT-DETR: Impact of Depth and Regularization under environmental conditions

arXiv:2605.08136v1 Announce Type: cross Abstract: Visual perception plays a central role in competitive robotics, where environmental variations can directly affect real-time detection performance. Th

Benchmarking Safety Risks of Knowledge-Intensive Reasoning under Malicious Knowledge Editing

arXiv:2605.10146v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on knowledge editing to support knowledge-intensive reasoning, but this flexibility also introduces criti

Benchmarking Sensor-Fault Robustness in Forecasting

model-releasesarxiv-cs-lg

arXiv:2605.10822v1 Announce Type: new Abstract: Cyber-physical system (CPS) forecasting models depend on sensor streams with noisy, biased, missing, or temporally misaligned readings, yet standard for

Benchmarking Transformer and xLSTM for Time-Series Forecasting of Heat Consumption

model-releasesarxiv-cs-lg

arXiv:2605.09722v1 Announce Type: new Abstract: Obtaining an accurate short-term forecasting for heat demand is an essential part of operating district heating networks cost-efficient and reliable. He

@BereznevKi20669 @ggerganov Yes I believe the real llama.cpp revolution is yet to happen at its full scale. As computers will have more RAM …

model-releasesgeorgi-gerganov--x

@BereznevKi20669 @ggerganov Yes I believe the real llama.cpp revolution is yet to happen at its full scale. As computers will have more RAM and models will improve, and *if* China will continue shippi

Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis

arXiv:2407.12173v2 Announce Type: replace-cross Abstract: Generative diffusion models have emerged as a powerful tool for high-quality image synthesis, yet their iterative nature demands significant c

BetaEdit: Null-Space Constrained Sequential Model Editing

arXiv:2605.09285v1 Announce Type: new Abstract: Null-space-based methods have garnered considerable attention in model editing by constraining updates to the null space of the pre-existing knowledge r

researcharxiv-cs-cl

Applications

Beyond Accuracy: Evaluating Posterior Fidelity of Diffusion Inverse Solvers

arXiv:2602.04189v2 Announce Type: replace Abstract: Uncertainty evaluation is critical in scientific and engineering inverse problems. However, existing benchmarks on Diffusion Inverse Solvers (DIS) p

applicationsarxiv-cs-lg

Beyond Accuracy: Evaluating Strategy Diversity in LLM Mathematical Reasoning

arXiv:2605.09292v1 Announce Type: new Abstract: Large language models now achieve high final-answer accuracy on mathematical reasoning benchmarks, but accuracy alone does not capture reasoning flexibi

Beyond Autonomy: A Dynamic Tiered AgentRunner Framework for Governable and Resilient Enterprise AI Execution

arXiv:2605.10223v1 Announce Type: new Abstract: Current large language model agent frameworks prioritize autonomy but lack the governability mechanisms required for enterprise deployment. High-risk wr

Beyond Bag-of-Patches: Learning Global Layout via Textual Supervision for Late-Interaction Visual Document Retrieval

arXiv:2605.08421v1 Announce Type: new Abstract: Visual Document Retrieval (VDR) models mostly rely on late interaction architectures, in which documents are represented by a set of local patch embeddi

local-aiarxiv-cs-cv

Beyond Continuity: Challenges of Context Switching in Multi-Turn Dialogue with LLMs

arXiv:2605.09268v1 Announce Type: cross Abstract: Users interacting with Large Language Models (LLMs) in a multi-turn conversation routinely refine their requests or pivot to new topics. LLMs, however

Beyond ESG Scores: Learning Dynamic Constraints for Sequential Portfolio Optimization

arXiv:2605.09310v1 Announce Type: new Abstract: ESG-aware portfolio optimization is increasingly important for sustainable capital allocation, yet most learning-based methods still operationalize ESG

Beyond Hard Writes and Rigid Preservation: Soft Recursive Least-Squares for Lifelong LLM Editing

arXiv:2601.15686v2 Announce Type: replace Abstract: Model editing updates a pre-trained LLM with new facts or rules without retraining while preserving unrelated behavior. In real deployment, edits ar

Beyond Isolation: A Unified Benchmark for General-Purpose Navigation

model-releasesarxiv-cs-ro

arXiv:2605.09441v1 Announce Type: new Abstract: The pursuit of general-purpose embodied agents is hindered by fragmented evaluation protocols that isolate navigation skills and fixate on specific robo

Beyond Language: Format-Agnostic Reasoning Subspaces in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.09496v1 Announce Type: new Abstract: Large language models represent the same reasoning in vastly different surface forms -- English prose, Python code, mathematical notation -- yet whether

Beyond Local Edits: Embedding-Virtualized Knowledge for Broader Evaluation and Preservation of Model Editing

model-releasesarxiv-cs-cl

arXiv:2602.01977v2 Announce Type: replace Abstract: Knowledge editing methods for large language models are commonly evaluated using predefined benchmarks that assess edited facts together with a limi