research

The Phantom of PCIe: Constraining Generative Artificial Intelligences for Practical Peripherals Trace Synthesizing

arXiv:2411.06376v3 Announce Type: replace-cross Abstract: Peripheral Component Interconnect Express (PCIe) is the de facto interconnect standard for high-speed peripherals and CPUs. The development of

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The problem with thinking you’re part Neanderthal

DGX agent

You’ve probably heard some version of this idea before: that many of us have an “inner Neanderthal.” That is to say, around 45,000 years ago, when Homo sapiens first arrived in Europe, they met member

researchmit-tech-review

14 Apr 2026

The role of memorization and knowledge is to cache & reuse past cognitive work. It should be leveraged as a way to speed up cognition, not a…

researchfrancois-chollet--x

Francois Chollet argues that memorization and knowledge function as a cache for previously completed cognitive work, allowing it to be reused efficiently rather than recomputed. The purpose of storing

The Wasserstein transform

arXiv:1810.07793v2 Announce Type: replace Abstract: We introduce the Wasserstein Transform (WT), a general unsupervised framework for updating distance structures on given data sets with the purpose o

The Weight of a Bit: EMFI Sensitivity Analysis of Embedded Deep Learning Models

arXiv:2602.16309v2 Announce Type: replace-cross Abstract: Fault injection attacks on embedded neural network models have been shown as a potent threat. Numerous works studied resilience of models from

@themaxburns give him time, it will get worse.

This appears to be a brief, informal reply post on X (formerly Twitter) directed at user @themaxburns, made in response to a conversation involving Yann LeCun, a prominent AI researcher and Chief AI S

researchyann-lecun--x

Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books

arXiv:2604.11435v1 Announce Type: cross Abstract: Character description generation is an important capability for narrative-focused applications such as summarization, story analysis, and character-dr

Time-Frequency Analysis for Neural Networks

arXiv:2512.15992v2 Announce Type: replace-cross Abstract: We develop a quantitative approximation theory for shallow neural networks using tools from time-frequency analysis. Working in weighted modul

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning

arXiv:2505.11737v4 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) have demonstrated impressive capabilities, their output quality remains inconsistent across various applica

Topology-Aware PAC-Bayesian Generalization Analysis for Graph Neural Networks

arXiv:2604.10553v1 Announce Type: new Abstract: Graph neural networks have demonstrated excellent applicability to a wide range of domains, including social networks, biological systems, recommendatio

Toward Accountable AI-Generated Content on Social Platforms: Steganographic Attribution and Multimodal Harm Detection

arXiv:2604.10460v1 Announce Type: cross Abstract: The rapid growth of generative AI has introduced new challenges in content moderation and digital forensics. In particular, benign AI-generated images

Towards an Appropriate Level of Reliance on AI: A Preliminary Reliance-Control Framework for AI in Software Engineering

arXiv:2604.10530v1 Announce Type: cross Abstract: How software developers interact with Artificial Intelligence (AI)-powered tools, including Large Language Models (LLMs), plays a vital role in how th

Towards Automated Solar Panel Integrity: Hybrid Deep Feature Extraction for Advanced Surface Defect Identification

arXiv:2604.10969v1 Announce Type: cross Abstract: To ensure energy efficiency and reliable operations, it is essential to monitor solar panels in generation plants to detect defects. It is quite labor

Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge

arXiv:2604.11679v1 Announce Type: new Abstract: Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is heterogeneous and noisy, and high-quality labels are

Towards Efficient Large Vision-Language Models: A Comprehensive Survey on Inference Strategies

arXiv:2603.27960v2 Announce Type: replace-cross Abstract: Although Large Vision Language Models (LVLMs) have demonstrated impressive multimodal reasoning capabilities, their scalability and deployment

Towards Green Wearable Computing: A Physics-Aware Spiking Neural Network for Energy-Efficient IMU-based Human Activity Recognition

arXiv:2604.10458v1 Announce Type: cross Abstract: Wearable IMU-based Human Activity Recognition (HAR) relies heavily on Deep Neural Networks (DNNs), which are burdened by immense computational and buf

Towards Proactive Information Probing: Customer Service Chatbots Harvesting Value from Conversation

arXiv:2604.11077v1 Announce Type: new Abstract: Customer service chatbots are increasingly expected to serve not merely as reactive support tools for users, but as strategic interfaces for harvesting

Towards Realistic 3D Emission Materials: Dataset, Baseline, and Evaluation for Emission Texture Generation

arXiv:2604.11006v1 Announce Type: new Abstract: 3D texture generation is receiving increasing attention, as it enables the creation of realistic and aesthetic texture materials for untextured 3D meshe

Towards Reasonable Concept Bottleneck Models

arXiv:2506.05014v2 Announce Type: replace-cross Abstract: We propose a novel, flexible, and efficient framework for designing Concept Bottleneck Models (CBMs) that enables practitioners to explicitly

TRACE: Thermal Recognition Attentive-Framework for CO2 Emissions from Livestock

arXiv:2604.09648v1 Announce Type: new Abstract: Quantifying exhaled CO2 from free-roaming cattle is both a direct indicator of rumen metabolic state and a prerequisite for farm-scale carbon accounting

Training Deep Visual Networks Beyond Loss and Accuracy Through a Dynamical Systems Approach

arXiv:2604.09716v1 Announce Type: cross Abstract: Deep visual recognition models are usually trained and evaluated using metrics such as loss and accuracy. While these measures show whether a model is

Training-Free Model Ensemble for Single-Image Super-Resolution via Strong-Branch Compensation

arXiv:2604.11564v1 Announce Type: new Abstract: Single-image super-resolution has progressed from deep convolutional baselines to stronger Transformer and state-space architectures, yet the correspond

Training-Free Multi-User Generative Semantic Communications via Null-Space Diffusion Sampling

arXiv:2405.09866v2 Announce Type: replace-cross Abstract: In recent years, novel communication strategies have emerged to face the challenges that the increased number of connected devices and the hig

Transactional Attention: Semantic Sponsorship for KV-Cache Retention

arXiv:2604.11288v1 Announce Type: new Abstract: At K=16 tokens (0.4% of a 4K context), every existing KV-cache compression method achieves 0% on credential retrieval. The failure mode is dormant token

TreeGrad-Ranker: Feature Ranking via O(L)-Time Gradients for Decision Trees

arXiv:2602.11623v2 Announce Type: replace Abstract: We revisit the use of probabilistic values, which include the well-known Shapley and Banzhaf values, to rank features for explaining the local predi

Trustworthy Feature Importance Avoids Unrestricted Permutations

arXiv:2604.11253v1 Announce Type: cross Abstract: Feature importance methods using unrestricted permutations are flawed due to extrapolation errors; such errors appear in all non-trivial variable impo

Turing or Cantor: That is the Question

arXiv:2604.10418v1 Announce Type: new Abstract: Alan Turing is considered as a founder of current computer science together with Kurt Godel, Alonzo Church and John von Neumann. In this paper multiple

UDAPose: Unsupervised Domain Adaptation for Low-Light Human Pose Estimation

arXiv:2604.10485v1 Announce Type: cross Abstract: Low-visibility scenarios, such as low-light conditions, pose significant challenges to human pose estimation due to the scarcity of annotated low-ligh

Uncertainty-Aware Web-Conditioned Scientific Fact-Checking

arXiv:2604.11036v1 Announce Type: cross Abstract: Scientific fact-checking is vital for assessing claims in specialized domains such as biomedicine and materials science, yet existing systems often ha

Uncertainty-Based Ensemble Learning in CMR Semantic Segmentation

arXiv:2502.09269v3 Announce Type: replace Abstract: Existing methods derive clinical functional metrics from ventricular semantic segmentation in cardiac cine sequences. While performing well on overa

Uncertainty-Guided Attention and Entropy-Weighted Loss for Precise Plant Seedling Segmentation

arXiv:2604.10823v1 Announce Type: new Abstract: Plant seedling segmentation supports automated phenotyping in precision agriculture. Standard segmentation models face difficulties due to intricate bac

Unfolding 3D Gaussian Splatting via Iterative Gaussian Synopsis

arXiv:2604.11685v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage

UniPROT: Uniform Prototype Selection via Partial Optimal Transport with Submodular Guarantees

arXiv:2604.10952v1 Announce Type: new Abstract: Selecting prototypical examples from a source distribution to represent a target data distribution is a fundamental problem in machine learning. Existin

Universal statistical signatures of evolution in artificial intelligence architectures

arXiv:2604.10571v1 Announce Type: cross Abstract: We test whether artificial intelligence architectural evolution obeys the same statistical laws as biological evolution. Compiling 935 ablation experi

Variational Visual Question Answering for Uncertainty-Aware Selective Prediction

arXiv:2505.09591v3 Announce Type: replace-cross Abstract: Despite remarkable progress in recent years, Vision Language Models (VLMs) remain prone to overconfidence and hallucinations on tasks such as

Vector Field Synthesis with Sparse Streamlines Using Diffusion Model

arXiv:2604.09838v1 Announce Type: new Abstract: We present a novel diffusion-based framework for synthesizing 2D vector fields from sparse, coherent inputs (i.e., streamlines) while maintaining physic

VeriSim: A Configurable Framework for Evaluating Medical AI Under Realistic Patient Noise

arXiv:2604.10441v1 Announce Type: new Abstract: Medical large language models (LLMs) achieve impressive performance on standardized benchmarks, yet these evaluations fail to capture the complexity of

VERTIGO: Visual Preference Optimization for Cinematic Camera Trajectory Generation

arXiv:2604.02467v2 Announce Type: replace-cross Abstract: Cinematic camera control relies on a tight feedback loop between director and cinematographer, where camera motion and framing are continuousl

Vestibular reservoir computing

arXiv:2604.09943v1 Announce Type: new Abstract: Reservoir computing (RC) is a computational framework known for its training efficiency, making it ideal for physical hardware implementations. However,

Vibe-driven model-based engineering

arXiv:2604.10645v1 Announce Type: cross Abstract: There is a pressing need for better development methods and tools to keep up with the growing demand and increasing complexity of new software systems

Video-based Heart Rate Estimation with Angle-guided ROI Optimization and Graph Signal Denoising

arXiv:2604.11395v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact heart rate measurement from facial videos, but its performance is significantly degraded by facia

VisText-Mosquito: A Unified Multimodal Dataset for Visual Detection, Segmentation, and Textual Explanation on Mosquito Breeding Sites

arXiv:2506.14629v3 Announce Type: replace-cross Abstract: Mosquito-borne diseases pose a major global health risk, requiring early detection and proactive control of breeding sites to prevent outbreak

Visual Late Chunking: An Empirical Study of Contextual Chunking for Efficient Visual Document Retrieval

arXiv:2604.10167v1 Announce Type: cross Abstract: Multi-vector models dominate Visual Document Retrieval (VDR) due to their fine-grained matching capabilities, but their high storage and computational

Volumetric Ergodic Control

arXiv:2511.11533v3 Announce Type: replace-cross Abstract: Ergodic control synthesizes optimal coverage behaviors over spatial distributions for nonlinear systems. However, existing formulations model

We are aware of issues impacting model availability via the Nous Portal and are working to restore service ASAP

Nous Research posted a status update on X acknowledging service disruptions affecting model availability through their Nous Portal. The announcement indicated the team was actively working to restore

researchnous-research--x

We benchmarked TranslateGemma against 5 other LLMs on subtitle translation across 6 languages. At first glance the numbers told a clean story, but then human QA added a chapter. [D]

researchr-machinelearning

This r/MachineLearning discussion post details a hands-on benchmark study in which TranslateGemma — Google's open translation model suite built on Gemma 3, available in 4B, 12B, and 27B sizes and cove

We will read histories of today’s US in a few decades and wonder how something like this could happen. Slowly allowing Polio and Measles to …

Yann LeCun shared or engaged with a post on X expressing concern about the erosion of public health infrastructure in the United States, specifically referencing the potential resurgence of eradicated

researchyann-lecun--x

What is the AC guidance for ICML? (Or: ICML qq thread) [D]

researchr-machinelearning

This r/MachineLearning Reddit thread serves as a community Q&A ('qq thread') focused on the Area Chair (AC) process for ICML, where researchers ask and answer questions about AC guidance, responsibili