All entries

Holly Bishop / The Independent: A BBC Question Time episode featured a panel with AI-generated historical figures like Churchill, intended to show AI images' “hyper-real and persuasive” nature — - BBC

industrytechmeme

A comparative study of transformer-based embeddings for topic coherence

model-releasesarxiv-cs-ai

arXiv:2605.28832v1 Announce Type: cross Abstract: Topic modeling is a branch of Natural Language Processing (NLP) that aims to organize large collections of texts into coherent groups according to wor

A Complete Loss Landscape Analysis of Regularized Deep Matrix Factorization

arXiv:2506.20344v3 Announce Type: replace-cross Abstract: Despite its wide range of applications across various domains, the optimization foundations of deep matrix factorization (DMF) remain largely

A Composable Multimodal Framework for cine CMR-Text-Driven Prediction of Heart Failure Outcomes

arXiv:2502.16548v3 Announce Type: replace-cross Abstract: Objective. Heart failure is one of the leading causes of death worldwide, with millions of deaths each year, according to data from the World

A Computational Method for Solving the Stochastic Joint Replenishment Problem in High Dimensions

arXiv:2511.11830v2 Announce Type: replace-cross Abstract: We consider a discrete-time formulation for a class of high-dimensional stochastic joint replenishment problems. First, we approximate the pro

A Deep Learning Iterative Framework for Sentinel-1 Stripmap Enhancement Based on Azimuth Doppler Decomposition

arXiv:2605.29088v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) imagery enables all-weather, day-and-night Earth observation; however, it remains difficult to interpret due to speckle n

researcharxiv-cs-cv

Agents

A Deep Learning Model of Mental Rotation Informed by Interactive VR Experiments

arXiv:2512.13517v2 Announce Type: replace-cross Abstract: Mental rotation -- the ability to compare objects seen from different viewpoints -- is a fundamental example of mental simulation and spatial

agentsarxiv-cs-lg

Agents

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

A Dual-Path Architecture for Scaling Compute and Capacity in LLMs

model-releasesarxiv-cs-cl

arXiv:2605.30202v1 Announce Type: new Abstract: Looped transformers apply a shared block multiple times and have emerged as a parameter-efficient route to scaling compute in language models. However,

A Full-Pipeline Framework for Evaluating Membership Inference Attacks in Machine Learning

arXiv:2605.29454v1 Announce Type: new Abstract: While Membership Inference Attacks (MIAs) are the prevailing method for identifying training data, their application has expanded into privacy auditing

A Fully Convolutional Approach to Denoising Structural Dynamics Data from X-Ray Photon Correlation Spectroscopy

arXiv:2605.29975v1 Announce Type: new Abstract: We present a fully convolutional denoising autoencoder (FC-DAE) for denoising two-time intensity-intensity correlation functions (C_2) in X-ray photon c

safetyarxiv-cs-lg

A Geometric View of SRC: Learning Representations for Stable Residual Inference

arXiv:2605.29673v1 Announce Type: cross Abstract: Reconstruction-based inference assigns a class by comparing class-wise reconstruction residuals; Sparse Representation Classification (SRC) is a canon

safetyarxiv-cs-cv

A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms

arXiv:2605.30313v1 Announce Type: new Abstract: Simulation-based RL for contemporary robot control is increasingly organized around GPU-resident simulation: physics, rollout collection, and learning a

safetyarxiv-cs-ro

A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search

arXiv:2602.11171v2 Announce Type: replace-cross Abstract: Fine-tuning Large Language Models (LLMs) with Low-Rank Adaptation (LoRA) offers a resource-efficient way to personalize or specialize. However

Applications

A Matter of Interest: Understanding Interestingness of Math Problems in Humans and Language Models

arXiv:2511.08548v2 Announce Type: replace Abstract: The evolution of mathematics is shaped importantly by interestingness: researchers choose which problems to pursue, and students choose which proble

applicationsarxiv-cs-ai

A Minimal Bifurcation Model of Load Imbalance in a Softmax Mixture-of-Experts Router

model-releasesarxiv-cs-ai

arXiv:2605.29121v1 Announce Type: cross Abstract: We propose a minimal dynamical model of adaptive softmax routing for a two-expert Mixture-of-Experts (MoE) layer. The model is obtained as a mean-fiel

A Modular Architecture for Typologically Controlled Lexicon Generation

arXiv:2605.28824v1 Announce Type: new Abstract: Constructing artificial lexicons that are pronounceable, typologically plausible, and semantically structured remains an open challenge in computational

safetyarxiv-cs-cl

A new completely parameter-free clustering algorithm for unsupervised classification of BATSE gamma-ray bursts

arXiv:2605.30175v1 Announce Type: cross Abstract: Cluster analysis is a widely applied machine learning technique to understand the existing patterns in the population of gamma-ray bursts (GRBs), in o

A new era of PC. 25.0528, 121.5990

This post from Nous Research references coordinates (likely geographic) and announces a new era in PC computing. The content likely discusses recent developments in personal computing technology, poss

researchnous-research--x

A Novel Tensor Product-Based Neural Network for Solving Partial Differential Equations

arXiv:2605.29688v1 Announce Type: new Abstract: This paper presents the Tensor Product Network (TPNet), a novel neural architecture for efficient and accurate function approximation and PDE solving. T

A Predictive Law for On-Policy Self-Distillation From World Feedback

arXiv:2605.30070v1 Announce Type: cross Abstract: Moving beyond simple scalar rewards toward richer world feedback is a natural path to more scalable RL post-training. On-policy self-distillation (OPS

safetyarxiv-cs-ai

A Progress-Aware Leader-Follower Midair Docking System for Dual-Drone Aerial Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.29410v1 Announce Type: new Abstract: Reliable midair docking between small unmanned aerial vehicles (UAVs) is essential for modular aerial cooperation and manipulation, but it requires prec

A Quotient Homology Theory of Representation in Neural Networks

arXiv:2502.01360v4 Announce Type: replace Abstract: Previous research has proven that the set of maps implemented by neural networks with a ReLU activation function is identical to the set of piecewis

A Review of Learning-Based Motion Planning: Toward a Data-Driven Optimal Control Approach

arXiv:2512.11944v2 Announce Type: replace-cross Abstract: Motion planning for autonomous driving (AD) faces a critical trade-off. While traditional rule-based pipelines offer verifiable safety and int

safetyarxiv-cs-ai

Tutorials

A shared playbook for trustworthy third party evaluations

This document outlines OpenAI's framework and recommendations for conducting independent third-party evaluations of AI systems to ensure trustworthiness and accountability. It establishes shared stand

tutorialsopenai

A Study on Question-Answer Dataset for LLM Safety Evaluation with a Focus on Illegal Activities

arXiv:2605.29340v1 Announce Type: new Abstract: In this paper, we discuss question-answer dataset for LLM safety evaluation, with a focus on illegal activities. Specifically, on the basis of manual an

safetyarxiv-cs-cl

A Survey on Recent Advances in Conversational Data Generation

arXiv:2405.13003v2 Announce Type: replace-cross Abstract: Recent advancements in conversational systems have significantly enhanced human-machine interactions across various domains. However, training

A Systematic Evaluation of Molecular Mixture Behavior Prediction

arXiv:2605.29698v1 Announce Type: new Abstract: Machine learning for molecular property prediction has focused largely on pure compounds, even though many practical applications depend on mixtures wit

Applications

A Theoretical and Experimental Study of a Novel Adaptive Learning Algorithm

arXiv:2605.29273v1 Announce Type: new Abstract: A crucial component of machine learning algorithms is minimizing loss functions with less computational cost and less oscillations. While adaptive learn

applicationsarxiv-cs-lg

A Training-Time Diagnostic for Generalization via the Log-Alignment Ratio

arXiv:2605.28975v1 Announce Type: new Abstract: We study the log-alignment ratio (LAR), a measure of parameter-activation alignment, introduced in parameterization theory. We reformulate it as the ove

A Triple-Modal Contrastive Learning Framework with Sequence, Graph, and 3D Features for Drug-Target Interaction Prediction

arXiv:2605.29926v1 Announce Type: new Abstract: Accurate prediction of drug-target interactions (DTI) is critical for drug discovery. Existing methods often rely on single-modal representations (e.g.,

A unified deeplearning framework for contrast-phase-specific virtual monochromatic imaging

arXiv:2605.29753v1 Announce Type: cross Abstract: Dual-energy CT (DECT) enables virtual monochromatic imaging (VMI) and improved contrast resolution, but its clinical adoption is limited by hardware c

Accelerating Constrained Decoding with Token Space Compression

arXiv:2605.29986v1 Announce Type: new Abstract: To guarantee that an LLM's outputs conform to a specified structure, context-free grammar (CFG) decoding engines force the selection of next tokens that

Local Ai

Accelerating HEVC Intra Partitioning via a CNN-Hierarchical Attention Transformer Hybrid

arXiv:2605.29063v1 Announce Type: cross Abstract: The recursive quad-tree partitioning in High Efficiency Video Coding (HEVC) incurs considerable computational overhead, with exhaustive rate-distortio

local-aiarxiv-cs-cv

Access Sets Matter: Budgeting Expert Reads for Scalable Weight-Space Model Merging

arXiv:2605.29489v1 Announce Type: new Abstract: Weight-space model merging is usually formulated as an algebraic operation on checkpoints, yet at LLM scale the limiting resource is often the set of ex

Applications

Accommodation Goes Both Ways: Studying Linguistic Convergence Between Humans and Language Models

arXiv:2605.29278v1 Announce Type: new Abstract: As LLMs become increasingly integrated into daily life, understanding how their presence will shape human linguistic behavior is an open question. We pr

applicationsarxiv-cs-cl

Achieving Linear Speedup for Composite Federated Learning

arXiv:2602.03357v2 Announce Type: replace Abstract: This paper proposes FedNMap, a normal map-based method for composite federated learning, where the objective consists of a smooth loss and a possibl

Active Continual Learning with Metaplastic Binary Bayesian Neural Networks

arXiv:2605.30198v1 Announce Type: new Abstract: Always-on edge systems must keep learning as conditions change under tight compute budgets and must detect unreliable predictions. Bayesian binary neura

Active Learning for Machine Learning Driven Molecular Dynamics

arXiv:2509.17208v3 Announce Type: replace Abstract: Machine-learned coarse-grained (CG) potentials are fast, but degrade over time when simulations reach under-sampled bio-molecular conformations, and

ActTraitBench: Quantifying the Knowledge-Decision Gap in Large Language Models via Human-Grounded Behavioral Validation

arXiv:2605.29791v1 Announce Type: new Abstract: While Large Language Models (LLMs) can convincingly simulate personas in explicit self-reports, they often deviate in implicit behavioral decisions, rev

safetyarxiv-cs-cl

Adapting Automotive Aerodynamics Surrogates to New Vehicle Families via Transfer Learning

arXiv:2605.27968v1 Announce Type: cross Abstract: Deploying Scientific Machine Learning surrogates in industrial CFD workflows requires adapting pretrained models to new vehicle families without large

Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation

model-releasesarxiv-cs-cl

arXiv:2605.29992v1 Announce Type: new Abstract: Sentence embeddings are a foundational component for semantic search, clustering, classification, and retrieval-augmented generation. This paper present

Adaptive Exponential Integration for Stable Gaussian Mixture Black-Box Variational Inference

arXiv:2601.14855v3 Announce Type: replace Abstract: Black-box variational inference (BBVI) with Gaussian mixture families offers a flexible approach for approximating complex posterior distributions w

Adaptive Interviewing for Persona Simulation in LLMs: Evidence-Grounded Reasoning Improves Decision Alignment

arXiv:2605.29458v1 Announce Type: cross Abstract: Accurately simulating the decisions of a specific individual remains challenging for large language models (LLMs), partly because persona information

safetyarxiv-cs-ai

Adaptive Targeted Dynamic Chunking for Tokenization-Free Hierarchical Model

arXiv:2605.30080v1 Announce Type: new Abstract: Tokenization-free hierarchical models are emerging as a promising alternative to traditional Large Language Models (LLMs), addressing inherent preproces

researcharxiv-cs-cl

AdaState: Self-Evolving Anchors for Streaming Video Generation

arXiv:2605.30349v1 Announce Type: new Abstract: Autoregressive video diffusion models generate streaming video by producing frames sequentially, conditioning each chunk on previously generated content

researcharxiv-cs-cv

Agents

Adobe’s conversational AI agent is a mediocre design intern

AI image tools rarely make me feel like I'm part of the creative process. They are, after all, mostly designed so that people with no design experience can type in a few words and get back a usable re

agentsthe-verge-ai

Adopt neq Adapt: Longitudinal Analyses of LLM Conversations in the Wild

arXiv:2605.29018v1 Announce Type: new Abstract: Although a growing body of research has begun to describe user--LLM interactions, the picture it paints is largely static; little is known about how ind