Search: “applications”

A Domain-Informed Multi-Objective Framework for EEG Channel Selection in Motor Imagery BCIs

arXiv:2605.29943v1 Announce Type: cross Abstract: Motor imagery (MI) classification using electroencephalography (EEG) signals is essential for advancing brain-computer interfaces (BCIs). Traditional

agentsarxiv-cs-lg

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Research

Aggregate Models, Not Explanations: Improving Feature Importance Estimation

DGX agent

arXiv:2602.11760v2 Announce Type: replace-cross Abstract: Feature-importance methods show promise in transforming machine learning models from predictive engines into tools for scientific discovery. H

researcharxiv-cs-lg

29 May 2026

Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models

arXiv:2605.30038v1 Announce Type: cross Abstract: Diffusion models generate highly realistic images but often struggle with precise text-image alignment. While recent post-training methods improve ali

Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation

arXiv:2605.29560v1 Announce Type: new Abstract: Parameterizing high-fidelity 'digital twins' of batteries is a critical yet challenging inverse problem that hinders the pace of battery innovation. Pre

Calibrating Generative Models to Distributional Constraints

arXiv:2510.10020v4 Announce Type: replace-cross Abstract: Generative models frequently suffer miscalibration, wherein statistics of the sampling distribution, such as the fraction of generations in a

Calibration Is Not Enough: Evaluating Confidence Estimation Under Language Variations

arXiv:2601.08064v2 Announce Type: replace Abstract: Confidence estimation (CE) indicates how reliable the answers of large language models are and impacts user trust and decision-making. Existing eval

safetyarxiv-cs-cl

CamC2V: Context-aware Controllable Video Generation

arXiv:2504.06022v3 Announce Type: replace Abstract: Recently, image-to-video (I2V) diffusion models have demonstrated impressive scene understanding and generative quality, incorporating image conditi

tutorialsarxiv-cs-cv

CLUBench: A Clustering Benchmark

model-releasesarxiv-cs-lg

arXiv:2605.29933v1 Announce Type: new Abstract: Clustering is a fundamental problem in data science with a long-standing research history, yielding numerous insightful algorithms. Despite this progres

Code-QA-Bench: Separating Code Reasoning from Documentation Memorization in Repository-Level QA

arXiv:2605.29277v1 Announce Type: cross Abstract: We present Code-QA-Bench, a fully automated framework for synthesizing repository-level code understanding benchmarks that separates genuine code comp

agentsarxiv-cs-ai

COMET: Concept Space Dissection of the Modality Gap in Audio-Text Multimodal Contrastive Embeddings

arXiv:2605.29628v1 Announce Type: cross Abstract: Contrastive Language-Audio Pretraining (CLAP) models are widely used for audio understanding and support modality-agnostic condition swapping in many

CompilerDream: Learning a Compiler World Model for General Code Optimization

arXiv:2404.16077v4 Announce Type: replace-cross Abstract: Effective code optimization in compilers is crucial for computer and software engineering. The success of these optimizations primarily depend

agentsarxiv-cs-lg

Conf-Gen: Conformal Uncertainty Quantification for Generative Models

arXiv:2605.28920v1 Announce Type: cross Abstract: Conformal prediction (CP) and its extension, conformal risk control (CRC), are established frameworks for quantifying uncertainty in supervised machin

Connecting Independently Trained Modes via Layer-Wise Connectivity

model-releasesarxiv-cs-lg

arXiv:2505.02604v5 Announce Type: replace Abstract: Empirical studies have shown that continuous low-loss paths can be constructed between independently trained neural network models. This phenomenon,

Constructing efficient channels for ideal observers using the conjugate gradient method

arXiv:2605.29415v1 Announce Type: cross Abstract: Task-based assessment of image quality (IQ) is critically important for the design and optimization of medical imaging systems. Ideal observers, inclu

researcharxiv-cs-cv

DCFO: Density-Based Counterfactuals for Outliers -- Additional Material

arXiv:2512.10659v3 Announce Type: replace Abstract: Outlier detection identifies data points that significantly deviate from the majority of the data distribution. Explaining outliers is crucial for u

Deja View: Looping Transformers for Multi-View 3D Reconstruction

arXiv:2605.30215v1 Announce Type: new Abstract: Recent feed-forward 3D reconstruction transformers have scaled to over a billion parameters, following the broader trend of increasing model capacity in

safetyarxiv-cs-cv

Diffusion-based learning framework for Constrained Nonconvex Optimization with Weighted Bootstrapped Refinement

model-releasesarxiv-cs-lg

arXiv:2502.10330v4 Announce Type: replace Abstract: Recent advances in diffusion models show promising potential to accelerate nonconvex problem solving by leveraging their multimodality. However, mos

Distributed Non-Uniform Scaling Control of Multi-Agent Formation with Dynamic Agent Joining

arXiv:2605.29191v1 Announce Type: cross Abstract: Non-uniform scaling control of formation enables multi-agent systems to adjust their shape by scaling with different ratios along different coordinate

agentsarxiv-cs-ro

Domain-Informed Representation for Evolutionary Sieving in Integral and Module Lattices

arXiv:2605.29169v1 Announce Type: cross Abstract: Traditional cryptography, rooted in problems, e.g., integer factorisation or discrete log, is inevitably vulnerable to a fully operational quantum com

Domain-Specific Data Synthesis for LLMs via Minimal Sufficient Representation Learning

arXiv:2605.30039v1 Announce Type: new Abstract: Large Language Models have demonstrated remarkable progress in general-purpose capabilities and can achieve strong performance in specific domains throu

tutorialsarxiv-cs-ai

Draw a path that a drone can follow https://x.com/bilawalsidhu/status/2059419767417487718?s=20

model-releasesgoogle-ai--x

This post likely describes a tool or system for planning autonomous drone flight paths, possibly involving visualization or interactive path-drawing interfaces. It may demonstrate how users can create

EMAG: Differentiable 4D Gaussian Mixture Splatting for EEG Spatial Super-Resolution

arXiv:2605.29731v1 Announce Type: new Abstract: High-density electroencephalography (HD-EEG) enables fine-grained measurement of cortical activity but requires expensive hardware and lengthy setup tim

Empathic Prompting: Non-Verbal Context Integration for Multimodal LLM Conversations

arXiv:2510.20743v2 Announce Type: replace-cross Abstract: We present Empathic Prompting, a novel framework for multimodal human-AI interaction that enriches Large Language Model (LLM) conversations wi

ExDBSCAN: Explaining DBSCAN with Counterfactual Reasoning -- Additional Material

arXiv:2605.30225v1 Announce Type: new Abstract: Clustering is an unsupervised technique for grouping data points by similarity. While explainability methods exist for supervised machine learning, they

FreeForm: Reduced-Order Deformable Simulation from Particle-Based Skinning Eigenmodes

arXiv:2605.29318v1 Announce Type: cross Abstract: We present a novel formulation for mesh-free, reduced-order simulation of deformable hyperelastic objects. Existing work in reduced-order elastodynami

researcharxiv-cs-cv

From Rubrics to Reliable Scores: Evidence-Grounded Text Evaluation with LLM Judges

arXiv:2601.08654v2 Announce Type: replace-cross Abstract: Rubric-based text evaluation increasingly uses large language models (LLMs) as scalable judges, but aligning frozen black-box models with huma

Tools

Function invocations now billed per unit

Vercel updated its billing model to charge for serverless function invocations on a per-unit basis rather than previous pricing structures. This change affects how customers are charged for executing

toolsvercel-blog

GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling

arXiv:2605.28835v1 Announce Type: cross Abstract: Large Language Models (LLMs) extend their capabilities through function-calling (FC), which relies on training data with high quality, diversity, and

agentsarxiv-cs-ai

Hallucination Detection-Guided Preference Optimization for Clinical Summarization

arXiv:2605.28910v1 Announce Type: cross Abstract: Large language models (LLMs) have shown promise on summarization tasks, but they often produce hallucinations, which are unsupported or incorrect stat

Honeyval: A Comprehensive Evaluation Framework for LLM-powered HTTP Honeypots

arXiv:2605.29963v1 Announce Type: cross Abstract: Honeypots are decoy systems mimicking real system components designed to defend against cyber attacks. Recently, LLMs increasingly serve as simulation

agentsarxiv-cs-ai

How Braintrust turns customer requests into code with Codex

Braintrust leverages OpenAI's Codex model to automatically convert customer requests and natural language specifications into functional code, streamlining the software development process. This appli

model-releasesopenai

How to Relieve Distribution Shifts in Semantic Segmentation for Off-Road Environments

arXiv:2605.29599v1 Announce Type: cross Abstract: Semantic segmentation is crucial for autonomous navigation in off-road environments, enabling precise classification of surroundings to identify trave

agentsarxiv-cs-cv

Hardware

How Together AI built the world’s fastest speech-to-text stack

Together AI developed an optimized speech-to-text system focused on achieving the fastest processing speeds through technical innovations in their inference stack and model optimization. The approach

hardwaretogether-ai-blog

Inspectorch: Efficient rare event exploration in solar observations

arXiv:2602.20316v2 Announce Type: replace-cross Abstract: The Sun is observed in unprecedented detail, enabling studies of its activity on very small spatiotemporal scales. However, the large volume o

researcharxiv-cs-cv

Jailbreaking and Mitigation of Vulnerabilities in Large Language Models

arXiv:2410.15236v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have transformed artificial intelligence by advancing natural language understanding and generation, enabling app

safetyarxiv-cs-ai

Joint Angle Estimation with Customized Wristband Based on Online Incremental Learning

arXiv:2605.29771v1 Announce Type: new Abstract: Intelligent wearable technology plays an increasingly important role in human-computer interaction, motion, and health monitoring. To ensure comfort and

researcharxiv-cs-ro

Knowing What to Solve Before How: Preplan Empowered LLM Mathematical Reasoning

arXiv:2605.30245v1 Announce Type: new Abstract: Current plan-based reasoning methods improve large language models (LLMs) by inserting a planning stage before execution, giving rise to the question ri

tutorialsarxiv-cs-cl

Learning Robust and Task-Invariant Functional Representation from fMRI through Siamese Self-Supervised Learning

arXiv:2605.28990v1 Announce Type: new Abstract: Functional magnetic resonance imaging (fMRI) is a powerful tool for investigating human brain function. However, the high cost of data acquisition and t

tutorialsarxiv-cs-lg

Tools

Links to original sources: https://simonwillison.net/2026/May/27/product-market-fit/#the-ai-failure-stories-around-this-are-pretty-thin

Simon Willison comments on the relative scarcity of well-documented AI product failure stories, suggesting that despite widespread predictions of AI disappointment, there are surprisingly few detailed

toolssimon-willison--x

Mask the Target: A Plug-and-Play Regularizer Against LoRA Forgetting

arXiv:2605.29498v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become one of the most widely used fine-tuning mechanisms for adapting large language models to new domains, tasks, and u

safetyarxiv-cs-cl

MATANet: A Multi-context Attention and Taxonomy-Aware Network for Fine-Grained Underwater Recognition of Marine Species

arXiv:2601.03729v2 Announce Type: replace Abstract: Fine-grained recognition of marine organisms is important for ecological research, biodiversity monitoring, habitat conservation, and evidence-based

safetyarxiv-cs-cv

MEC: Machine-Learning-Assisted Generalized Entropy Calibration for Semi-Supervised Mean Estimation

arXiv:2604.05446v2 Announce Type: replace-cross Abstract: Obtaining high-quality labels is costly, whereas unlabeled covariates are often abundant, motivating semi-supervised inference methods with re

MechELK: A Mechanistic Interpretability Framework for Eliciting Latent Knowledge in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.28825v1 Announce Type: new Abstract: Large language models (LLMs) frequently encode factual and reasoning knowledge in their internal representations that is not faithfully reflected in the

Local Ai

MediHive: A Decentralized Agent Collective for Medical Reasoning

arXiv:2603.27150v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized medical reasoning tasks, yet single-agent systems often falter on complex, interdisciplinary proble

local-aiarxiv-cs-ai

Modeling Hierarchical Thinking in Large Reasoning Models

arXiv:2510.22437v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) solve complex tasks by generating long Chain-of-Thought (CoT) sequences; however, the emergent dynamics governing reas

safetyarxiv-cs-ai

MPDocBench-Parse: Benchmarking Practical Multi-page Document Parsing

arXiv:2605.22100v2 Announce Type: replace Abstract: Document parsing converts visually rich documents into machine-readable structured representations, forming a crucial foundation for information sys

Neural Operator-Based Surrogate Model for CFD:Helical Coil Steam Generator in Small Modular Reactor

arXiv:2605.30277v1 Announce Type: new Abstract: Real-time thermal-hydraulic simulation is essential for digital twin (DT) technology that supports the safe and efficient operation of small modular rea

safetyarxiv-cs-lg

NeuroEdge: Real-Time Hand Gesture Recognition with High-Density EMG Using Deep Learning at the Edge

arXiv:2605.29326v1 Announce Type: new Abstract: High-density electromyography (HD-EMG) has emerged as a powerful modality for decoding fine-grained neuromuscular activity, enabling real-time neural-ma