All entries

Anomaly Detection in IEC-61850 GOOSE Networks: Evaluating Unsupervised and Temporal Learning for Real-Time Intrusion Detection

arXiv:2604.14233v1 Announce Type: cross Abstract: The IEC-61850 GOOSE protocol underpins time-critical communication in modern digital substations but lacks native security mechanisms, leaving it vuln

Model Releases

Anonpsy: A Graph-Based Framework for Structure-Preserving De-identification of Psychiatric Narratives

DGX agent

arXiv:2601.13503v2 Announce Type: replace Abstract: Psychiatric narratives encode patient identity not only through explicit identifiers but also through idiosyncratic life events embedded in their cl

model-releasesarxiv-cs-cl

17 Apr 2026

Anthropic launches Claude Design to speed up graphic design projects

model-releasessiliconangle

The latest addition to Anthropic PBC’s product portfolio is Claude Design, a tool that enables users to generate visual assets with prompts. The company launched the offering into public preview today

Anthropic’s new cybersecurity model could get it back in the government’s good graces

model-releasesthe-verge-ai

The Trump administration has spent nearly two months fighting with AI company Anthropic. It's dubbed the company a 'RADICAL LEFT, WOKE COMPANY' full of 'Leftwing nut jobs' and a menace to national sec

Agents

APEX-MEM: Agentic Semi-Structured Memory with Temporal Reasoning for Long-Term Conversational AI

arXiv:2604.14362v1 Announce Type: new Abstract: Large language models still struggle with reliable long-term conversational memory: simply enlarging context windows or applying naive retrieval often i

agentsarxiv-cs-cl

Applying an Agentic Coding Tool for Improving Published Algorithm Implementations

model-releasesarxiv-cs-ai

arXiv:2604.13109v1 Announce Type: cross Abstract: We present a two-stage pipeline for AI-assisted improvement of published algorithm implementations. In the first stage, a large language model with re

Arrow — local SAM contract CSV + SQLite; optional Ollama for JSON “why fit” & summarize (format: json)

Based on the Reddit post title, Arrow appears to be a tool for processing SAM (Supplier Agreement Management) contracts stored in CSV and SQLite formats, with optional integration of Ollama to generat

local-air-ollama

ArrowGEV: Grounding Events in Video via Learning the Arrow of Time

arXiv:2601.06559v2 Announce Type: replace Abstract: Grounding events in videos serves as a fundamental capability in video analysis. While Vision Language Models (VLMs) are increasingly employed for t

researcharxiv-cs-cv

Industry

Artemis II pilot talks about what it was really like to fly and land in Orion

Artemis II pilot Victor Glover described reentry as dramatically intense and 'at least 10 times wilder' than a rocket launch, calling it the most phenomenal part of spaceflight. Commander Reid Wiseman

industryars-technica

ASGNet: Adaptive Spectrum Guidance Network for Automatic Polyp Segmentation

arXiv:2604.14755v1 Announce Type: new Abstract: Early identification and removal of polyps can reduce the risk of developing colorectal cancer. However, the diverse morphologies, complex backgrounds a

researcharxiv-cs-cv

Assessing the Performance-Efficiency Trade-off of Foundation Models in Probabilistic Electricity Price Forecasting

arXiv:2604.14739v1 Announce Type: new Abstract: Large-scale renewable energy deployment introduces pronounced volatility into the electricity system, turning grid operation into a complex stochastic o

Assessing the Potential of Masked Autoencoder Foundation Models in Predicting Downhole Metrics from Surface Drilling Data

arXiv:2604.15169v1 Announce Type: new Abstract: Oil and gas drilling operations generate extensive time-series data from surface sensors, yet accurate real-time prediction of critical downhole metrics

Assessment Design in the AI Era: A Method for Identifying Items Functioning Differentially for Humans and Chatbots

model-releasesarxiv-cs-ai

arXiv:2603.23682v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) in education raises profound challenges for assessment design. To adapt assessments to the

Asynchronous Probability Ensembling for Federated Disaster Detection

arXiv:2604.14450v1 Announce Type: new Abstract: Quick and accurate emergency handling in Disaster Decision Support Systems (DDSS) is often hampered by network latency and suboptimal application accura

Hardware

At SemiAnalysis, we're quite tired of the minimalist style webapps and landing pages that have become so commonplace lately. Today, we're in…

At SemiAnalysis, we're quite tired of the minimalist style webapps and landing pages that have become so commonplace lately. Today, we're introducing Minecraft mode on inferencex dot com so that you c

hardwaredylan-patel--x

Atropos: Improving Cost-Benefit Trade-off of LLM-based Agents under Self-Consistency with Early Termination and Model Hotswap

arXiv:2604.15075v1 Announce Type: cross Abstract: Open-weight Small Language Models(SLMs) can provide faster local inference at lower financial cost, but may not achieve the same performance level as

local-aiarxiv-cs-lg

Attention-Gated Convolutional Networks for Scanner-Agnostic Quality Assessment

arXiv:2604.15059v1 Announce Type: new Abstract: Motion artifacts present a significant challenge in structural MRI (sMRI), often compromising clinical diagnostics and large-scale automated analysis. W

local-aiarxiv-cs-cv

Tutorials

Attention to Mamba: A Recipe for Cross-Architecture Distillation

arXiv:2604.14191v1 Announce Type: new Abstract: State Space Models (SSMs) such as Mamba have become a popular alternative to Transformer models, due to their reduced memory consumption and higher thro

tutorialsarxiv-cs-cl

Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models

arXiv:2508.15396v2 Announce Type: replace Abstract: The increasing adoption of large language models (LLMs) has raised serious concerns about their reliability and trustworthiness. As a result, a grow

researcharxiv-cs-cl

AutoRAN: Automated Hijacking of Safety Reasoning in Large Reasoning Models

arXiv:2505.10846v3 Announce Type: replace Abstract: This paper presents AutoRAN, the first framework to automate the hijacking of internal safety reasoning in large reasoning models (LRMs). At its cor

Auxiliary Finite-Difference Residual-Gradient Regularization for PINNs

arXiv:2604.14472v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) are often selected by a single scalar loss even when the quantity of interest is more specific. We study a hybr

Awakening Dormant Experts:Counterfactual Routing to Mitigate MoE Hallucinations

arXiv:2604.14246v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) models have achieved remarkable scalability, yet they remain vulnerable to hallucinations, particularly when processing

b8821

Release b8821 of llama.cpp includes improvements to the server component, allowing pinning of media markers via the LLAMA_MEDIA_MARKER environment variable and making the get_media_marker() function t

b8822

b8822 is a release of llama.cpp that adds q5_K gemm and gemv kernels for Adreno GPUs . The release includes builds for multiple platforms including macOS, Linux, Windows, iOS, and openEuler distributi

b8823

b8823 is a build release of llama.cpp, the C/C++ implementation for LLM inference that enables efficient language model execution locally and in the cloud. Based on the rapid development cycle of the

b8824

b8824 is a llama.cpp release that optimizes HMX matmul operations, including refactoring functions to use size_t for tile counts and improving readability of core matrix multiplication routines. Relea

b8825

Release b8825 of llama.cpp, released on April 17, 2026, includes updates to media marker handling where the `get_media_marker()` function now checks the LLAMA_MEDIA_MARKER environment variable on firs

b8826

Release b8826 of llama.cpp implements improvements to media marker handling for template application, with changes to how `get_media_marker()` checks and uses the LLAMA_MEDIA_MARKER setting, making te

b8829

b8829 is a release build of llama.cpp , a C/C++ framework for running large language models locally. Notable in this release was a significant size difference compared to the preceding build b8828 , t

b8831

Release b8831 of llama.cpp includes CI improvements for Android ARM64 build and release, along with a fix for the server to respect the ignore EOS flag. The release provides compiled binaries for mult

b8832

b8832 is a recent build release of llama.cpp from April 17, 2026 . Llama.cpp is a C/C++ implementation for running large language model inference efficiently on consumer hardware with minimal setup. T

b8833

Release b8833 of llama.cpp includes updates to the ggml-webgpu backend, fixing compiler warnings and refactoring FlashAttention encoding, along with workflow improvements and precision adjustments for

Industry

Banks Don’t Have an AI Problem – They Have a Data Platform Problem

Banks face challenges implementing AI not due to lack of AI technology, but rather due to fragmented, siloed data platforms that prevent effective data integration and accessibility. The article argue

industrydatabricks

Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models

arXiv:2601.21003v2 Announce Type: replace Abstract: Large Language Models usually put more emphasis on accuracy and therefore, will guess even when not certain about the prediction, which is especiall

researcharxiv-cs-ai

Applications

Bayesian Optimization with Gaussian Processes to Accelerate Stationary Point Searches

arXiv:2603.10992v3 Announce Type: replace-cross Abstract: Building local surrogates to accelerate stationary point searches on potential energy surfaces spans decades of effort. Done correctly, surrog

applicationsarxiv-cs-lg

Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios

model-releasesarxiv-cs-ro

arXiv:2604.15202v1 Announce Type: new Abstract: Coverage path planning on irregular hexagonal grids is relevant to maritime surveillance, search and rescue and environmental monitoring, yet classical

Benchmarking Linguistic Adaptation in Comparable-Sized LLMs: A Study of Llama-3.1-8B, Mistral-7B-v0.1, and Qwen3-8B on Romanized Nepali

model-releasesarxiv-cs-cl

arXiv:2604.14171v1 Announce Type: new Abstract: Romanized Nepali, the Nepali language written in the Latin alphabet, is the dominant medium for informal digital communication in Nepal, yet it remains

Benchmarking Optimizers for MLPs in Tabular Deep Learning

arXiv:2604.15297v1 Announce Type: new Abstract: MLP is a heavily used backbone in modern deep learning (DL) architectures for supervised learning on tabular data, and AdamW is the go-to optimizer used

Best of both worlds: Stochastic & adversarial best-arm identification

arXiv:2604.14860v1 Announce Type: cross Abstract: We study bandit best-arm identification with arbitrary and potentially adversarial rewards. A simple random uniform learner obtains the optimal rate o

Best Ollama model for n8n workflows (RAG, file handling, reasoning) + hardware requirements?

Models like Qwen3 and Llama 3.2 are commonly used for n8n RAG workflows , with selection depending on use case requirements. Running Ollama models locally requires at least 16 GB of RAM on your device

local-air-ollama

Safety

Between a Rock and a Hard Place: The Tension Between Ethical Reasoning and Safety Alignment in LLMs

arXiv:2509.05367v4 Announce Type: replace-cross Abstract: Large Language Model safety alignment predominantly operates on a binary assumption that requests are either safe or unsafe. This classificati

safetyarxiv-cs-ai

Beyond Augmentation: Cross-Modal Transformer Fusion with Bi-directional Attention for Low-Data Aneurysm Screening

arXiv:2512.22185v2 Announce Type: replace Abstract: Intracranial aneurysm rupture causes subarachnoid hemorrhage with mortality near 50%, making early detection critical. Although CTA enables rapid sc

local-aiarxiv-cs-cv

Safety

Beyond Importance Sampling: Rejection-Gated Policy Optimization

arXiv:2604.14895v1 Announce Type: new Abstract: We propose a new perspective on policy optimization: rather than reweighting all samples by their importance ratios, an optimizer should select which sa

safetyarxiv-cs-lg

Applications

Beyond Independent Frames: Latent Attention Masked Autoencoders for Multi-View Echocardiography

arXiv:2604.15096v1 Announce Type: new Abstract: Echocardiography is a widely used modality for cardiac assessment due to its non-invasive and cost-effective nature, but the sparse and heterogeneous sp

applicationsarxiv-cs-cv

Agents

Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation

arXiv:2601.07338v2 Announce Type: replace Abstract: Large Language Models (LLMs) have significantly advanced Machine Translation (MT), applying them to linguistically complex domains-such as Social Ne

agentsarxiv-cs-cl

Beyond Prompts: Unconditional 3D Inversion for Out-of-Distribution Shapes

arXiv:2604.14914v1 Announce Type: new Abstract: Text-driven inversion of generative models is a core paradigm for manipulating 2D or 3D content, unlocking numerous applications such as text-based edit

researcharxiv-cs-cv

Beyond the Laplacian: Doubly Stochastic Matrices for Graph Neural Networks

arXiv:2604.15069v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) conventionally rely on standard Laplacian or adjacency matrices for structural message passing. In this work, we substitute

Beyond Translation: Evaluating Mathematical Reasoning Capabilities of LLMs in Sinhala and Tamil

arXiv:2602.14517v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved strong results in mathematical reasoning, and are increasingly deployed as tutoring and learning support

researcharxiv-cs-cl