Search: “applications”

A Compact and Efficient 1.251 Million Parameter Machine Learning CNN Model PD36-C for Plant Disease Detection: A Case Study

model-releasesarxiv-cs-ai

arXiv:2604.11332v1 Announce Type: cross Abstract: Deep learning has markedly advanced image based plant disease diagnosis as improved hardware and dataset quality have enabled increasingly accurate ne

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A Dual Cross-Attention Graph Learning Framework For Multimodal MRI-Based Major Depressive Disorder Detection

DGX agent

arXiv:2604.10116v1 Announce Type: cross Abstract: Major depressive disorder (MDD) is a prevalent mental disorder associated with complex neurobiological changes that cannot be fully captured using a s

researcharxiv-cs-ai

14 Apr 2026

A Minimal Model of Representation Collapse: Frustration, Stop-Gradient, and Dynamics

arXiv:2604.09979v1 Announce Type: cross Abstract: Self-supervised representation learning is central to modern machine learning because it extracts structured latent features from unlabeled data and e

AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruption

model-releasesarxiv-cs-cl

arXiv:2508.03793v2 Announce Type: replace Abstract: Long-context large language models (LLMs), such as Gemini-2.5-Pro and Claude-Sonnet-4, are increasingly used to empower advanced AI systems, includi

Continuous PT-Symmetry Breaking as a Design Variable for Giant Altermagnetic Spin Splitting

arXiv:2604.10173v1 Announce Type: cross Abstract: Magnetic point-group analysis classifies altermagnets but returns only a binary symmetry verdict, leaving spin-splitting energy (SSE) inaccessible wit

Delving Aleatoric Uncertainty in Medical Image Segmentation via Vision Foundation Models

arXiv:2604.10963v1 Announce Type: new Abstract: Medical image segmentation supports clinical workflows by precisely delineating anatomical structures and lesions. However, medical image datasets medic

DIB-OD: Preserving the Invariant Core for Robust Heterogeneous Graph Adaptation via Decoupled Information Bottleneck and Online Distillation

arXiv:2604.10882v1 Announce Type: cross Abstract: Graph Neural Network pretraining is pivotal for leveraging unlabeled graph data. However, generalizing across heterogeneous domains remains a major ch

ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation

arXiv:2502.18026v3 Announce Type: replace-cross Abstract: Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging t

Heterogeneous Connectivity in Sparse Networks: Fan-in Profiles, Gradient Hierarchy, and Topological Equilibria

model-releasesarxiv-cs-lg

arXiv:2604.10560v1 Announce Type: new Abstract: Profiled Sparse Networks (PSN) replace uniform connectivity with deterministic, heterogeneous fan-in profiles defined by continuous, nonlinear functions

Inductive Reasoning for Temporal Knowledge Graphs with Emerging Entities

arXiv:2604.10164v1 Announce Type: new Abstract: Reasoning on Temporal Knowledge Graphs (TKGs) is essential for predicting future events and time-aware facts. While existing methods are effective at ca

LogitDynamics: Reliable ViT Error Detection from Layerwise Logit Trajectories

arXiv:2604.10643v1 Announce Type: new Abstract: Reliable confidence estimation is critical when deploying vision models. We study error prediction: determining whether an image classifier's output is

Tutorials

Probabilistic Prediction of Neural Dynamics via Autoregressive Flow Matching

arXiv:2604.11178v1 Announce Type: cross Abstract: Forecasting neural activity in response to naturalistic stimuli remains a key challenge for understanding brain dynamics and enabling downstream neuro

tutorialsarxiv-cs-lg

Reasoning as Data: Representation-Computation Unity and Its Implementation in a Domain-Algebraic Inference Engine

arXiv:2604.10908v1 Announce Type: new Abstract: Every existing knowledge system separates storage from computation. We show this separation is unnecessary and eliminate it. In a standard triple is_a(A

Hardware

Record-Remix-Replay: Hierarchical GPU Kernel Optimization using Evolutionary Search

arXiv:2604.11109v1 Announce Type: cross Abstract: As high-performance computing and AI workloads become increasingly dependent on GPUs, maintaining high performance across rapidly evolving hardware ge

hardwarearxiv-cs-ai

SafeConstellations: Mitigating Over-Refusals in LLMs Through Task-Aware Representation Steering

arXiv:2508.11290v3 Announce Type: replace Abstract: LLMs increasingly exhibit over-refusal behavior, where safety mechanisms cause models to reject benign instructions that seemingly resemble harmful

safetyarxiv-cs-cl

ShapShift: Explaining Model Prediction Shifts with Subgroup Conditional Shapley Values

arXiv:2604.11200v1 Announce Type: cross Abstract: Changes in input distribution can induce shifts in the average predictions of machine learning models. Such prediction shifts may impact downstream bu

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

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

WearBCI Dataset: Understanding and Benchmarking Real-World Wearable Brain-Computer Interfaces Signals

model-releasesarxiv-cs-ai

arXiv:2604.09649v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) have opened new platforms for human-computer interaction, medical diagnostics, and neurorehabilitation. Wearable BCI

Local Ai

WebLLM: A High-Performance In-Browser LLM Inference Engine

arXiv:2412.15803v2 Announce Type: replace-cross Abstract: Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-gra

local-aiarxiv-cs-ai

X-SYS: A Reference Architecture for Interactive Explanation Systems

arXiv:2602.12748v3 Announce Type: replace Abstract: The explainable AI (XAI) research community has proposed numerous technical methods, yet deploying explainability as systems remains challenging: In

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need

model-releasesarxiv-cs-lg

arXiv:2604.08749v1 Announce Type: new Abstract: How many of a neural network's parameters actually encode task-specific information? We investigate this question with LottaLoRA, a training paradigm in

AdaCubic: An Adaptive Cubic Regularization Optimizer for Deep Learning

arXiv:2604.09437v1 Announce Type: new Abstract: A novel regularization technique, AdaCubic, is proposed that adapts the weight of the cubic term. The heart of AdaCubic is an auxiliary optimization pro

DeFakeQ: Enabling Real-Time Deepfake Detection on Edge Devices via Adaptive Bidirectional Quantization

model-releasesarxiv-cs-cv

arXiv:2604.08847v1 Announce Type: new Abstract: Deepfake detection has become a fundamental component of modern media forensics. Despite significant progress in detection accuracy, most existing metho

Dual Mamba for Node-Specific Representation Learning: Tackling Over-Smoothing with Selective State Space Modeling

arXiv:2511.06756v3 Announce Type: replace Abstract: Over-smoothing remains a fundamental challenge in deep Graph Neural Networks (GNNs), where repeated message passing causes node representations to b

EXAONE 4.5 Technical Report

model-releasesarxiv-cs-cl

arXiv:2604.08644v1 Announce Type: new Abstract: This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integr

Generative Simulation for Policy Learning in Physical Human-Robot Interaction

arXiv:2604.08664v1 Announce Type: new Abstract: Developing autonomous physical human-robot interaction (pHRI) systems is limited by the scarcity of large-scale training data to learn robust robot beha

safetyarxiv-cs-ro

Hierarchical Alignment: Enforcing Hierarchical Instruction-Following in LLMs through Logical Consistency

arXiv:2604.09075v1 Announce Type: new Abstract: Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system poli

safetyarxiv-cs-cl

Natural Riemannian gradient for learning functional tensor networks

model-releasesarxiv-cs-lg

arXiv:2604.09263v1 Announce Type: cross Abstract: We consider machine learning tasks with low-rank functional tree tensor networks (TTN) as the learning model. While in the case of least-squares regre

TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice

model-releasesarxiv-cs-cl

arXiv:2604.08948v1 Announce Type: new Abstract: While Large Language Models (LLMs) excel in various general domains, they exhibit notable gaps in the highly specialized, knowledge-intensive, and legal

harness engineering > prompt engineering prompts get you 80% there the last 20% — tool routing, memory retrieval, retry logic, evals — thats…

Harrison Chase, co-founder of LangChain, argues that while prompt engineering is foundational and can get you 80% of the way to a functional AI system, the remaining 20% of engineering effort involves

agentsharrison-chase--x

12 Apr 2026

Syntheses

Wiki Lint Report — 2026-04-12

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Automated lint: 34 errors, 0 warnings, 3 info

12 Apr 2026

Concepts

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Auto-generated index of all companies mentioned across the wiki.

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PhD or Masters for Computational Cognitive Science [R]

researchr-machinelearning

This Reddit post on r/MachineLearning discusses the decision between pursuing a PhD versus a Master's degree for those interested in computational cognitive science, an interdisciplinary field combini

Thanks for another banger! Incredibly easy to read as always. It reminded me of your Daytona conference distinction about the different type…

Harrison Chase, co-founder and CEO of LangChain, received positive feedback from a follower referencing a distinction he made at a Daytona conference, suggesting he regularly shares accessible and wel

agentsharrison-chase--x

your harness = your memory if you'd rather read in blog form, link here: https://blog.langchain.com/your-harness-your-memory/

LangChain's concept of 'your harness = your memory' explores how the surrounding infrastructure and framework around an AI agent effectively functions as its memory system. The post likely discusses h

agentsharrison-chase--x

AI-Driven Marine Robotics: Emerging Trends in Underwater Perception and Ecosystem Monitoring

arXiv:2509.01878v2 Announce Type: replace-cross Abstract: Marine ecosystems face increasing pressure due to climate change, driving the need for scalable, AI-powered monitoring solutions to inform eff

EEG2Vision: A Multimodal EEG-Based Framework for 2D Visual Reconstruction in Cognitive Neuroscience

arXiv:2604.08063v1 Announce Type: new Abstract: Reconstructing visual stimuli from non-invasive electroencephalography (EEG) remains challenging due to its low spatial resolution and high noise, parti

Lighting-grounded Video Generation with Renderer-based Agent Reasoning

arXiv:2604.07966v1 Announce Type: new Abstract: Diffusion models have achieved remarkable progress in video generation, but their controllability remains a major limitation. Key scene factors such as

agentsarxiv-cs-cv

LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification

arXiv:2502.17421v4 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) can now process extremely long contexts, efficient inference over these extended inputs has become increasingl

The Weaponization of Computer Vision: Tracing Military-Surveillance Ties through Conference Sponsorship

arXiv:2604.07803v1 Announce Type: cross Abstract: Computer vision, a core domain of artificial intelligence (AI), is the field that enables the computational analysis, understanding, and generation of

What’s new with Google Cloud

model-releasesgoogle-cloud-ai

Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more. Tip: Not

Guardrails at the gateway: Securing AI inference on GKE with Model Armor

Enterprises are rapidly moving AI workloads from experimentation to production on Google Kubernetes Engine (GKE), using its scalability to serve powerful inference endpoints. However, as these models

safetygoogle-cloud-ai

9 Apr 2026

Tutorials

The founder of a $4B inference company says that if you're building agents, foundational models could become your IP. According to @lqiao, 9…

The founder of a $4B inference company says that if you're building agents, foundational models could become your IP. According to @lqiao, 90% of the world's data is still private and locked inside ap

tutorialssonya-huang--x

9 Apr 2026

Experimenting with GPUs: GKE managed DRANET and Inference Gateway AI Deployment

model-releasesgoogle-cloud-ai

Building and serving models on infrastructure is a strong use case for businesses. In Google Cloud, you have the ability to design your AI infrastructure to suit your workloads. Recently, I experiment

8 Apr 2026

Modify and load custom VBIOS on Windows and Linux, on Blackwell 2.0 (RTX 50 Series)/Ada(RTX 40 Series)/Ampere (RTX 30 Series) without flasing, for example to lower power limits (and which cards were tested)

model-releasesr-localllama

Hello guys, hoping you're doing fine. Today I want to share something that may affect your cards (? I have released 3 tools: A way to modify VBIOSes, so you can increase power limit, voltage, NVVDD of

17 Oct 2026

Industry

Neuralink president DJ Seo says Elon’s aggressive schedules are rigorous first-principles engineering, and an all-green-light schedule shows…

Neuralink president DJ Seo says Elon’s aggressive schedules are rigorous first-principles engineering, and an all-green-light schedule shows 80 to 90% of delays are just assumed “What I’ve learned is

industryelon-musk--x

17 Oct 2026

A Model Ensemble-Based Post-Processing Framework for Fairness-Aware Prediction