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time to help builders own their intelligence, open everything 🤝 the data produced and Experiential Memory gained from every agent interacti…

model-releasesharrison-chase--x

time to help builders own their intelligence, open everything 🤝 the data produced and Experiential Memory gained from every agent interaction is the one of the most valuable things you can own to impr

11 Apr 2026

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Research

When in doubt, 'hermes update'

DGX agent

Nous Research shared a tip or reminder encouraging users to run 'hermes update' when experiencing issues or uncertainty with their Hermes model or related tooling, suggesting this command resolves com

researchnous-research--x

11 Apr 2026

A Data-Informed Variational Clustering Framework for Noisy High-Dimensional Data

arXiv:2604.06864v1 Announce Type: cross Abstract: Clustering in high-dimensional settings with severe feature noise remains challenging, especially when only a small subset of dimensions is informativ

Tutorials

A Severity-Based Curriculum Learning Strategy for Arabic Medical Text Generation

arXiv:2604.06365v1 Announce Type: cross Abstract: Arabic medical text generation is increasingly needed to help users interpret symptoms and access general health guidance in their native language. Ne

tutorialsarxiv-cs-ai

A Spatial-Spectral-Frequency Interactive Network for Multimodal Remote Sensing Classification

arXiv:2510.04628v2 Announce Type: replace Abstract: Deep learning-based methods have achieved significant success in remote sensing Earth observation data analysis. Numerous feature fusion techniques

Adaptive Depth-converted-Scale Convolution for Self-supervised Monocular Depth Estimation

arXiv:2604.07665v1 Announce Type: new Abstract: Self-supervised monocular depth estimation (MDE) has received increasing interests in the last few years. The objects in the scene, including the object

Adaptive Prompt Structure Factorization: A Framework for Self-Discovering and Optimizing Compositional Prompt Programs

arXiv:2604.06699v1 Announce Type: cross Abstract: Automated prompt optimization is crucial for eliciting reliable reasoning from large language models (LLMs), yet most API-only prompt optimizers itera

researcharxiv-cs-lg

All is not lost. Duckerton is still possible. Here is Seedance 2.0 with the same prompt.

model-releasesethan-mollick--x

All is not lost. Duckerton is still possible. Here is Seedance 2.0 with the same prompt. Media My most popular Sora video was “an Elaborate regency romance where everyone is wearing a live duck for a

Tutorials

Analyzing Multimodal Interaction Strategies for LLM-Assisted Manipulation of 3D Scenes

arXiv:2410.22177v2 Announce Type: replace-cross Abstract: As more applications of large language models (LLMs) for 3D content for immersive environments emerge, it is crucial to study user behaviour t

tutorialsarxiv-cs-ai

ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection

arXiv:2510.07927v2 Announce Type: replace Abstract: Anomaly detection plays a pivotal role in manufacturing quality control, yet its application is constrained by limited abnormal samples and high man

AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views

arXiv:2604.07041v1 Announce Type: cross Abstract: Text-to-SQL is the task of translating natural language queries into executable SQL for a given database, enabling non-expert users to access structur

Bias Redistribution in Visual Machine Unlearning: Does Forgetting One Group Harm Another?

arXiv:2604.08111v1 Announce Type: cross Abstract: Machine unlearning enables models to selectively forget training data, driven by privacy regulations such as GDPR and CCPA. However, its fairness impl

safetyarxiv-cs-cv

Busemann energy-based attention for emotion analysis in Poincare discs

arXiv:2604.06752v1 Announce Type: new Abstract: We present EmBolic - a novel fully hyperbolic deep learning architecture for fine-grained emotion analysis from textual messages. The underlying idea is

researcharxiv-cs-lg

Can VLMs Unlock Semantic Anomaly Detection? A Framework for Structured Reasoning

arXiv:2510.18034v2 Announce Type: replace-cross Abstract: Autonomous driving systems remain critically vulnerable to the long-tail of rare, out-of-distribution semantic anomalies. While VLMs have emer

agentsarxiv-cs-ai

CHiQPM: Calibrated Hierarchical Interpretable Image Classification

arXiv:2511.20779v2 Announce Type: replace Abstract: Globally interpretable models are a promising approach for trustworthy AI in safety-critical domains. Alongside global explanations, detailed local

local-aiarxiv-cs-lg

ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation

arXiv:2603.17812v2 Announce Type: replace-cross Abstract: Recent video diffusion models achieve high-quality generation through recurrent frame processing where each frame generation depends on previo

researcharxiv-cs-ai

ConvoLearn: A Dataset for Fine-Tuning Dialogic AI Tutors

arXiv:2601.08950v3 Announce Type: replace Abstract: Despite their growing adoption in education, LLMs remain misaligned with the core principle of effective tutoring: the dialogic construction of know

Decompose, Look, and Reason: Reinforced Latent Reasoning for VLMs

arXiv:2604.07518v1 Announce Type: new Abstract: Vision-Language Models often struggle with complex visual reasoning due to the visual information loss in textual CoT. Existing methods either add the c

safetyarxiv-cs-cl

Does ollama cloud pro will generate token faster than free?

Ollama Cloud offers Free, Pro ($20/month), and Max ($100/month) subscription tiers for cloud-hosted inference, but token generation speed depends on model size, architecture, and hardware optimiza...

local-air-ollama

Domain-Contextualized Inference: A Computable Graph Architecture for Explicit-Domain Reasoning

arXiv:2604.04344v2 Announce Type: replace Abstract: We establish a computation-substrate-agnostic inference architecture in which domain is an explicit first-class computational parameter. This produc

Drifting Fields are not Conservative

arXiv:2604.06333v1 Announce Type: new Abstract: Drifting models generate high-quality samples in a single forward pass by transporting generated samples toward the data distribution using a vector val

researcharxiv-cs-lg

Evaluating Low-Light Image Enhancement Across Multiple Intensity Levels

arXiv:2511.15496v2 Announce Type: replace Abstract: Imaging in low-light environments is challenging due to reduced scene radiance, which leads to elevated sensor noise and reduced color saturation. M

Flux2 Klein 2 stage upscale?

local-air-stablediffusion

A 2-stage upscaling workflow using FLUX.2 Klein in ComfyUI combines the model's image-editing capabilities with a secondary upscaler (such as SeedVR2) to produce high-resolution outputs — for examp...

FMI@SU ToxHabits: Evaluating LLMs Performance on Toxic Habit Extraction in Spanish Clinical Texts

arXiv:2604.06403v1 Announce Type: cross Abstract: The paper presents an approach for the recognition of toxic habits named entities in Spanish clinical texts. The approach was developed for the ToxHab

Tutorials

Generalization Under Scrutiny: Cross-Domain Detection Progresses, Pitfalls, and Persistent Challenges

arXiv:2604.08230v1 Announce Type: new Abstract: Object detection models trained on a source domain often exhibit significant performance degradation when deployed in unseen target domains, due to vari

tutorialsarxiv-cs-cv

Governing frontier general-purpose AI in the public sector: adaptive risk management and policy capacity under uncertainty through 2030

arXiv:2604.06215v1 Announce Type: cross Abstract: The governance of frontier general-purpose artificial intelligence has become a public-sector problem of institutional design, not merely a technical

safetyarxiv-cs-ai

Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation

arXiv:2604.08046v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current res

researcharxiv-cs-cl

HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns

arXiv:2601.10198v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona s

safetyarxiv-cs-cl

@IeloEmanuele is on a roll! you can now use claude code's advisor strategy with @LangChain agents because langchain/deepagents are provider …

model-releasesharrison-chase--x

@IeloEmanuele is on a roll! you can now use claude code's advisor strategy with @LangChain agents because langchain/deepagents are provider agnostic, you can use different providers for your advisor a

im excited about agent harnesses because i think are the first stable agent abstractions we can build on top (which is why we're investing s…

im excited about agent harnesses because i think are the first stable agent abstractions we can build on top (which is why we're investing so much in deepagents) we always wanted to run llms in a loop

agentsharrison-chase--x

Improving Image Coding for Machines through Optimizing Encoder via Auxiliary Loss

arXiv:2402.08267v3 Announce Type: replace Abstract: Image coding for machines (ICM) aims to compress images for machine analysis using recognition models rather than human vision. Hence, in ICM, it is

researcharxiv-cs-cv

KITE: Keyframe-Indexed Tokenized Evidence for VLM-Based Robot Failure Analysis

arXiv:2604.07034v1 Announce Type: cross Abstract: We present KITE, a training-free, keyframe-anchored, layout-grounded front-end that converts long robot-execution videos into compact, interpretable t

Learning Debt and Cost-Sensitive Bayesian Retraining: A Forecasting Operations Framework

arXiv:2604.06438v1 Announce Type: cross Abstract: Forecasters often choose retraining schedules by convention rather than by an explicit decision rule. This paper gives that decision a posterior-space

Learning to Search: A Decision-Based Agent for Knowledge-Based Visual Question Answering

arXiv:2604.07146v2 Announce Type: replace Abstract: Knowledge-based visual question answering (KB-VQA) requires vision-language models to understand images and use external knowledge, especially for r

agentsarxiv-cs-cv

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

LiteParse is the best document parsing library for coding agents. It's free, fast, integrates natively with the LLM's native visual understa…

model-releasesjerry-liu--x

LiteParse is the best document parsing library for coding agents. It's free, fast, integrates natively with the LLM's native visual understanding capabilities, and comes with support for 50+ formats a

Loop, Think, & Generalize: Implicit Reasoning in Recurrent-Depth Transformers

arXiv:2604.07822v1 Announce Type: new Abstract: We study implicit reasoning, i.e. the ability to combine knowledge or rules within a single forward pass. While transformer-based large language models

researcharxiv-cs-cl

Lumbermark: Resistant Clustering by Chopping Up Mutual Reachability Minimum Spanning Trees

arXiv:2604.07143v1 Announce Type: new Abstract: We introduce Lumbermark, a robust divisive clustering algorithm capable of detecting clusters of varying sizes, densities, and shapes. Lumbermark iterat

Matrix Profile for Time-Series Anomaly Detection: A Reproducible Open-Source Benchmark on TSB-AD

arXiv:2604.02445v2 Announce Type: replace Abstract: Matrix Profile (MP) methods are an interpretable and scalable family of distance-based methods for time-series anomaly detection, but strong benchma

Mitigating Distribution Sharpening in Math RLVR via Distribution-Aligned Hint Synthesis and Backward Hint Annealing

model-releasesarxiv-cs-cl

arXiv:2604.07747v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) can improve low-k reasoning accuracy while narrowing solution coverage on challenging math que

Modernizing Amdahl's Law: How AI Scaling Laws Shape Computer Architecture

arXiv:2603.20654v4 Announce Type: replace-cross Abstract: Classical Amdahl's Law conceptualized the limit of speedup for an era of fixed serial-parallel decomposition and homogeneous replication. Mode

researcharxiv-cs-ai

MSCT: Differential Cross-Modal Attention for Deepfake Detection

arXiv:2604.07741v1 Announce Type: new Abstract: Audio-visual deepfake detection typically employs a complementary multi-modal model to check the forgery traces in the video. These methods primarily ex

safetyarxiv-cs-cv

Applications

MSG Score: Automated Video Verification for Reliable Multi-Scene Generation

arXiv:2411.19121v2 Announce Type: replace-cross Abstract: While text-to-video diffusion models have advanced significantly, creating coherent long-form content remains unreliable due to stochastic sam

applicationsarxiv-cs-ai

Applications

MV-SAM3D: Adaptive Multi-View Fusion for Layout-Aware 3D Generation

arXiv:2603.11633v2 Announce Type: replace Abstract: Recent unified 3D generation models have made remarkable progress in producing high-quality 3D assets from a single image. Notably, layout-aware app

applicationsarxiv-cs-cv

New changes at CivitAI

local-air-stablediffusion

In 2025, CivitAI underwent several significant platform changes. In April–May 2025, CivitAI tightened rules around extreme/illegal content and real-person likenesses. After its payment processor...

ODYN: An All-Shifted Non-Interior-Point Method for Quadratic Programming in Robotics and AI

arXiv:2602.16005v2 Announce Type: replace-cross Abstract: We introduce ODYN, a novel all-shifted primal-dual non-interior-point quadratic programming (QP) solver designed to efficiently handle challen

PeReGrINE: Evaluating Personalized Review Fidelity with User Item Graph Context

model-releasesarxiv-cs-cl

arXiv:2604.07788v1 Announce Type: cross Abstract: We introduce PeReGrINE, a benchmark and evaluation framework for personalized review generation grounded in graph-structured user--item evidence. PeRe

Physical Knot Classification Beyond Accuracy: A Benchmark and Diagnostic Study

arXiv:2603.23286v3 Announce Type: replace Abstract: Physical knot classification is a fine-grained task in which the intended cue is rope crossing structure, but high accuracy may still come from appe