All entries

A Comparative Study on Affective Cues in Text Embeddings Across Psychological Emotion Theories

arXiv:2606.29068v1 Announce Type: cross Abstract: Text encoders are known for their utility in natural language processing, as they are able to efficiently compress inputs into dense vectors while pre

Research

A Conditional GAN for Tabular Data Generation with Probabilistic Sampling of Latent Subspaces

DGX agent

arXiv:2508.00472v2 Announce Type: replace Abstract: The tabular form constitutes the standard way of representing data in relational database systems and spreadsheets. But, similarly to other forms, t

researcharxiv-cs-lg

30 Jun 2026

A conversation is all it takes to launch powerful ComfyUI workflows. This showcase demonstrates how Comfy MCP can generate, refine, and iter…

A conversation is all it takes to launch powerful ComfyUI workflows. This showcase demonstrates how Comfy MCP can generate, refine, and iterate on creative assets using natural language. To try this w

agentscomfyui--x

A Deep Multiscale Neural Network for Accurate Neurological Disorder Detection from MRI Scans and Real-Time Web Deployment

arXiv:2606.29106v1 Announce Type: cross Abstract: Neurological disorders involve diverse pathologies of the brain and nervous system, making early and accurate detection essential. While many deep CNN

A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel

arXiv:2111.10722v4 Announce Type: replace-cross Abstract: We propose a novel deterministic sampling method, EVI-MMD, to approximate a target distribution rho^* by minimizing the kernel discrepancy, al

A Diagnostic Framework and Multi-Evaluator Audit of Evaluator-Driven Preference Dynamics in Self-Adapting LLM Agents

model-releasesarxiv-cs-cl

arXiv:2606.29719v1 Announce Type: cross Abstract: Measurements of proprietary LLM evaluators can become invalid within weeks -- we document one case and provide the diagnostic framework to detect it.

Tutorials

A Distributionally Robust Framework for Learned Reconstructions in Inverse Problems

arXiv:2606.30230v1 Announce Type: cross Abstract: Learned reconstruction operators for inverse problems are typically trained under a fixed noise model, and generalize poorly when the distribution dur

tutorialsarxiv-cs-lg

A Dual-domain Refinement Network with FBP-based Jacobian Learning for Sparse-view Dual-Energy CT Material Decomposition

arXiv:2606.30159v1 Announce Type: new Abstract: Dual-energy CT (DECT) exploits attenuation differences across different X-ray spectra to provide richer material information and has been widely used in

A French OSCE Dialogue Dataset and Controllable Virtual Patient System for Clinical Training

arXiv:2606.28526v1 Announce Type: new Abstract: The clinical and communication skills of medical students are commonly assessed through Objective Structured Clinical Examinations (OSCEs), which consis

researcharxiv-cs-cl

Applications

A Good Talk Does not Look Like a Summary, It Teaches You! Measuring Takeaways from Paper-to-Video Talks

arXiv:2606.28531v1 Announce Type: cross Abstract: Automatically generated videos from scientific papers are increasingly used for education and research dissemination. However, existing evaluation met

applicationsarxiv-cs-cl

A Gravitational Interpretation of Fine-Tuning Reversion

arXiv:2606.28525v1 Announce Type: cross Abstract: Fine-tuning on harmless data can partially undo behaviors acquired earlier in training. Safety can erode under benign post-alignment updates, unlearne

safetyarxiv-cs-ai

A great read from @LangChain Best framing I've seen for agent architecture. Every non-model piece like the filesystem, sandbox, compaction, …

A great read from @LangChain Best framing I've seen for agent architecture. Every non-model piece like the filesystem, sandbox, compaction, Ralph loops exists to patch a specific model limitation. htt

agentsharrison-chase--x

Local Ai

A Hybrid Framework For Crypto-Ransomware Detection In Enterprise Shared Storage

arXiv:2606.30586v1 Announce Type: cross Abstract: Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints. Consequent

local-aiarxiv-cs-lg

A Hybrid Framework for Song Lyric Annotation Based on Human-LLM Alignment

arXiv:2606.29273v1 Announce Type: cross Abstract: Emotion recognition of song lyrics is a challenging task since lyrics may not necessarily align with the overall emotion of a song. As a result, lyric

safetyarxiv-cs-ai

A Kernel Fisher Discriminant Analysis-Based Tree Ensemble Classifier: KFDA Forest

arXiv:2606.29053v1 Announce Type: new Abstract: In general, an ensemble classifier is more accurate than a single classifier. In this study, we propose an ensemble classifier called the kernel Fisher

Applications

A Knowledge Theory of Capital:The Value of Natural and Artificial Intelligence, Volume 1

arXiv:2606.18288v2 Announce Type: replace-cross Abstract: This volume develops a knowledge theory of capital for economies in which productive capacity increasingly resides in software, data, models,

applicationsarxiv-cs-ai

A Linear Matching Bandit Approach to Online Multi-Human Multi-Robot Teaming

arXiv:2606.29221v1 Announce Type: new Abstract: We address the problem of online multi-human multi-robot teaming through the lens of a linear matching bandit framework, where a learner assigns robots

A living map of everything your Hermes agent has learned; every memory & skill Press play to watch it unfold, @NousResearch Copy yours into …

This post from Nous Research demonstrates a visualization tool or system that maps the accumulated knowledge, memories, and skills learned by a Hermes AI agent during its training or operation. The in

agentsnous-research--x

A Machine-Verified Proof of a Quantum-Optimization Conjecture

arXiv:2606.29687v1 Announce Type: cross Abstract: We report a machine-verified resolution of a problem open for over a decade in quantum optimization: the Farhi, Goldstone and Gutmann (FGG) conjecture

A Mathematical Optimization Approach for Expert-Informed Bayesian Best Subset Selection

arXiv:2606.29516v1 Announce Type: new Abstract: A central challenge in statistical modeling is identifying the subset of features that belong in the true regression model. The classical best subset se

A Mechanistic Study of Transformers Training Dynamics

arXiv:2410.24050v3 Announce Type: replace Abstract: Large-scale pretraining of transformers has been central to the success of foundation models. However, the scale of those models limits our understa

A Morse-Bott Framework for Blind Inverse Problems: Local Recovery Guarantees and the Failure of the MAP

arXiv:2508.02923v3 Announce Type: replace Abstract: Maximum A Posteriori (MAP) estimation is a cornerstone framework for blind inverse problems, where an image and a forward operator are jointly estim

A multi-architecture study of specificity refinement and false-positive mechanism analysis in prostate MRI

model-releasesarxiv-cs-cv

arXiv:2606.29977v1 Announce Type: cross Abstract: Objectives: To characterize residual false positives in prostate MRI detection, and to evaluate a lightweight post-hoc refinement head for case-level

A Multi Center Breast FNAC Whole-Slide Cytology Dataset for AI-Assisted Patch-Wise Classification Using C1 to C5 Reporting Categories

arXiv:2606.30209v1 Announce Type: cross Abstract: We present a multi center breast fine needle aspiration cytology (FNAC) dataset designed for patch wise classification using C1 to C5 reporting labels

A Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure Diagnosis

arXiv:2606.29193v1 Announce Type: cross Abstract: LLM-based agents are reshaping microservice operations into AgentOps, where benchmarks are key to evaluating failure diagnosis over multimodal observa

A Multi-task Mixture of Experts Framework for Malware Classification, Packing Detection, and Family Attribution

arXiv:2606.30572v1 Announce Type: cross Abstract: Malware classification remains a challenging problem due to its inherent heterogeneity, the presence of packed binaries, and the diverse distribution

A Neuroimaging Simulation Framework for Developing and Evaluating Causal AI

arXiv:2606.28684v1 Announce Type: cross Abstract: Causally linking disease-related factors to image-derived biomarkers provides a powerful pathway to understanding disease mechanisms. Despite growing

A Novel Latent-Class Attack and its Detection by Class Subspace Orthogonalization

arXiv:2606.29112v1 Announce Type: new Abstract: Deep learning, which in general relies on voluminous amounts of training data, is vulnerable to data poisoning attacks, including error-generic attacks

Local Ai

A Path-Space Formulation of Prediction in World Models: From a Single Action to Prediction, Planning, and Irreversibility

arXiv:2606.28751v1 Announce Type: new Abstract: We propose a path-space formulation of prediction in AI world models. Rather than sequences of one-step conditional distributions, we argue that a world

local-aiarxiv-cs-lg

A Physics-Grounded Benchmark for Multi-Agent Dynamics in World Models

model-releasesarxiv-cs-cv

arXiv:2606.28757v1 Announce Type: new Abstract: Generative world models hold immense promise as scalable simulators for autonomous systems, particularly for synthesizing rare but safety-critical multi

A Point Cloud Transformer for Remote Monitoring and Automated Assessment of Physical Rehabilitation Exercises

arXiv:2606.30309v1 Announce Type: new Abstract: Rehabilitation exercises are essential in restoring lost physical functions of patients suffering from various diseases (e.g., Parkinson's, back pain).

A Posteriori Error Analysis for Decoupled Neural Approximations of Fully Coupled FBSDEs with Control Mismatch

arXiv:2606.29474v1 Announce Type: cross Abstract: This paper develops an a posteriori error analysis framework for decoupled neural approximations of fully coupled forward--backward stochastic differe

A Probabilistic Approach to Trajectory-Based Optimal Experimental Design

model-releasesarxiv-cs-lg

arXiv:2601.11473v2 Announce Type: replace-cross Abstract: We present a novel probabilistic approach for optimal experimental path design. In this approach a discrete path optimization problem is defin

A Query-Driven Communication-Efficient Digital Twins Design for Autonomous Driving

arXiv:2606.28384v1 Announce Type: cross Abstract: Digital twins (DTs) have become a potential technology to perform risk-free simulation of physical entities for deterministic and high-reliability ser

agentsarxiv-cs-ai

A Self-Supervised Learning Framework for Video Encoding Complexity Clustering

arXiv:2606.29166v1 Announce Type: cross Abstract: Adaptive video streaming is a widely used technique for delivering video content over the internet. One of the key challenges is determining the optim

A Stochastic--Geometric Theory of Scaling Laws in Grokking

arXiv:2606.30388v1 Announce Type: cross Abstract: Delayed generalization (ie~grokking) refers to the phenomenon in which a neural network fits its training data early in training but only begins to ge

Local Ai

A study from @Stanford showed that 71.3% of chatgpt queries could be accurately answered by a local model. I suspect a major part of enterpr…

A study from @Stanford showed that 71.3% of chatgpt queries could be accurately answered by a local model. I suspect a major part of enterprise AI workloads could be run locally too for free (compared

local-aiclem-delangue--x

Industry

A study of 22K US companies shows those spending most heavily on AI are adding workers faster than peers, but most gains are among tech companies and startups (Financial Times)

Financial Times: A study of 22K US companies shows those spending most heavily on AI are adding workers faster than peers, but most gains are among tech companies and startups — Study of 22,000 US com

industrytechmeme

A Systems-Level Analysis of Sensitivity, Robustness, and Stability in Retrieval-Augmented Generation

arXiv:2606.28337v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are often evaluated using final answer accuracy, even though their failures can originate from preprocess

A Task-Driven and Quality-Assured Agent Framework for SAR Data Generation

arXiv:2606.28896v1 Announce Type: cross Abstract: Synthetic aperture radar (SAR) data augmentation is important for improving the generalization of data-driven SAR interpretation models, yet practical

agentsarxiv-cs-ai

A Theoretical Interpretation of In-Context Learning via Probabilistic Modeling

arXiv:2606.28926v1 Announce Type: cross Abstract: In-context learning (ICL) is an emerging paradigm that employs the semantic information inherent in large language models (LLMs) for generating answer

Hardware

A Trainable-by-Parts Operator Learning Framework: Bridging DeepONet and Karhunen-Loeve Expansions for Large-Scale Applications

arXiv:2606.28519v1 Announce Type: new Abstract: Training operator-learning models for large-scale problems governed by partial differential equations (PDEs) is challenging due to the curse of dimensio

hardwarearxiv-cs-lg

A Unified Framework for Multi-Contact Path Planning in the Rolling Robot Systems

arXiv:2606.29065v1 Announce Type: new Abstract: Rolling motion planning is challenging because rolling contact imposes nonholonomic constraints and the configuration evolves on a curved manifold. The

researcharxiv-cs-ro

a very cool Harbor x LangSmith flow I love to help you “look at the data”: 1. you do evals or rollouts for RL 2. all reward metrics and trac…

a very cool Harbor x LangSmith flow I love to help you “look at the data”: 1. you do evals or rollouts for RL 2. all reward metrics and traces and rollouts get automatically propulates into Experiment

agentsharrison-chase--x

A Zero-Shot Deep Image Prior Framework for Denoising and Deconvolution in Fluorescence Microscopy

arXiv:2606.28431v1 Announce Type: cross Abstract: Fluorescence microscopy images are degraded by noise and diffraction-induced blur, which compromise structural fidelity and limit quantitative analysi

A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions

arXiv:2606.28943v1 Announce Type: new Abstract: Learning to bid in repeated multi-unit auctions with bandit feedback poses a fundamental challenge. Existing methods often rely on rigid explore-then-ex

safetyarxiv-cs-cl

AB-RAG: Adaptive Budgeted Retrieval-Augmented Generation for Reliable Question Answering

arXiv:2606.29090v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has become the standard way to ground large language models in external knowledge, yet most systems retrieve a fi

safetyarxiv-cs-ai

AccelAes: Accelerating Diffusion Transformers for Training-Free Aesthetic-Enhanced Image Generation

arXiv:2603.12575v2 Announce Type: replace Abstract: Diffusion Transformers (DiTs) are a dominant backbone for high-fidelity text-to-image generation due to strong scalability and alignment at high res

safetyarxiv-cs-cv