Search: “models”

From Boundaries to Semantics: Prompt-Guided Multi-Task Learning for Petrographic Thin-section Segmentation

arXiv:2604.14805v1 Announce Type: new Abstract: Grain-edge segmentation (GES) and lithology semantic segmentation (LSS) are two pivotal tasks for quantifying rock fabric and composition. However, thes

safetyarxiv-cs-cv

Human

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Tutorials

From Procedural Skills to Strategy Genes: Towards Experience-Driven Test-Time Evolution

DGX agent

arXiv:2604.15097v1 Announce Type: cross Abstract: This beta technical report asks how reusable experience should be represented so that it can function as effective test-time control and as a substrat

tutorialsarxiv-cs-cl

17 Apr 2026

Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD

arXiv:2601.10237v2 Announce Type: replace Abstract: Differentially Private Stochastic Gradient Descent (DP-SGD) is the dominant paradigm for private training, but its fundamental limitations under wor

Gating Enables Curvature: A Geometric Expressivity Gap in Attention

arXiv:2604.14702v1 Announce Type: new Abstract: Multiplicative gating is widely used in neural architectures and has recently been applied to attention layers to improve performance and training stabi

GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification

arXiv:2604.14258v1 Announce Type: cross Abstract: Large language models are typically post-trained using supervised fine-tuning (SFT) and reinforcement learning (RL), yet effectively unifying efficien

safetyarxiv-cs-lg

Graph Theoretical Outlier Rejection for 4D Radar Registration in Feature-Poor Environments

arXiv:2604.14857v1 Announce Type: new Abstract: Automotive 4D imaging radar is well suited for operation in dusty and low-visibility environments, but scan registration remains challenging due to scan

researcharxiv-cs-ro

Industry

Grok 4.3 can Take in Video and Extract Audio files

Grok 4.3, an AI model by xAI, has been updated with multimodal capabilities enabling it to process video input and extract audio from video files. This enhancement expands Grok's functionality beyond

industryelon-musk--x

Hijacking online reviews: sparse manipulation and behavioral buffering in popularity-biased rating systems

arXiv:2604.13049v1 Announce Type: cross Abstract: Online reviews and recommendation systems help users navigate overwhelming choice, but they are vulnerable to self-reinforcing distortions. This paper

agentsarxiv-cs-ai

How Retrieved Context Shapes Internal Representations in RAG

arXiv:2602.20091v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) enhances large language models (LLMs) by conditioning generation on retrieved external documents, but the effec

How robots learn: A brief, contemporary history

Roboticists used to dream big but build small. They’d hope to match or exceed the extraordinary complexity of the human body, and then they’d spend their career refining robotic arms for auto plants.

tutorialsmit-tech-review

Applications

https://github.com/emollick/tower-of-babel

applicationsethan-mollick--x

Tower of Babel is a GitHub repository by researcher Ethan Mollick that likely explores how AI language models handle multilingual tasks and cross-language communication, potentially investigating chal

Integration of Deep Reinforcement Learning and Agent-based Simulation to Explore Strategies Counteracting Information Disorder

arXiv:2604.13047v1 Announce Type: cross Abstract: In recent years, the spread of fake news has triggered a growing interest in Information Disorders (ID) on social media, a phenomenon that has become

agentsarxiv-cs-ai

Hardware

LayerScope: Predictive Cross-Layer Scheduling for Efficient Multi-Batch MoE Inference on Legacy Servers

arXiv:2509.23638v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models face memory and PCIe latency bottlenecks when deployed on commodity hardware. Offloading expert weights to CPU memor

hardwarearxiv-cs-lg

Applications

Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation

arXiv:2604.15101v1 Announce Type: cross Abstract: Learning-to-Rank (LTR) is a supervised machine learning approach that constructs models specifically designed to order a set of items or documents bas

applicationsarxiv-cs-lg

ML-based approach to classification and generation of structured light propagation in turbulent media

arXiv:2604.14208v1 Announce Type: cross Abstract: This work develops machine learning approaches to classify structured light wave beams developing random speckle disturbances as they propagate throug

MLDAS: Machine Learning Dynamic Algorithm Selection for Software-Defined Networking Security

arXiv:2604.14957v1 Announce Type: cross Abstract: Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their per

Multi-Modal Manipulation via Multi-Modal Policy Consensus

arXiv:2509.23468v3 Announce Type: replace-cross Abstract: Effectively integrating diverse sensory modalities is crucial for robotic manipulation. However, the typical approach of feature concatenation

safetyarxiv-cs-lg

On the Creativity of AI Agents

arXiv:2604.13242v1 Announce Type: cross Abstract: Large language models (LLMs), particularly when integrated into agentic systems, have demonstrated human- and even superhuman-level performance across

agentsarxiv-cs-ai

One-shot Compositional 3D Head Avatars with Deformable Hair

arXiv:2604.14782v1 Announce Type: new Abstract: We propose a compositional method for constructing a complete 3D head avatar from a single image. Prior one-shot holistic approaches frequently fail to

One-shot learning for the complex dynamical behaviors of weakly nonlinear forced oscillators

arXiv:2604.15181v1 Announce Type: new Abstract: Extrapolative prediction of complex nonlinear dynamics remains a central challenge in engineering. This study proposes a one-shot learning method to ide

agentsarxiv-cs-lg

Prompt-to-Gesture: Measuring the Capabilities of Image-to-Video Deictic Gesture Generation

arXiv:2604.14953v1 Announce Type: new Abstract: Gesture recognition research, unlike NLP, continues to face acute data scarcity, with progress constrained by the need for costly human recordings or im

RACER: Retrieval-Augmented Contextual Rapid Speculative Decoding

arXiv:2604.14885v1 Announce Type: new Abstract: Autoregressive decoding in Large Language Models (LLMs) generates one token per step, causing high inference latency. Speculative decoding (SD) mitigate

Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization

arXiv:2601.20868v2 Announce Type: replace Abstract: Large Language Models (LLMs) have advanced the field of Combinatorial Optimization through automated heuristic generation. Instead of relying on man

Seen-to-Scene: Keep the Seen, Generate the Unseen for Video Outpainting

arXiv:2604.14648v1 Announce Type: new Abstract: Video outpainting aims to expand the visible content of a video beyond the original frame boundaries while preserving spatial fidelity and temporal cohe

SegWithU: Uncertainty as Perturbation Energy for Single-Forward-Pass Risk-Aware Medical Image Segmentation

arXiv:2604.15271v1 Announce Type: new Abstract: Reliable uncertainty estimation is critical for medical image segmentation, where automated contours feed downstream quantification and clinical decisio

Sentiment analysis for software engineering: How far can zero-shot learning (ZSL) go?

arXiv:2604.13826v1 Announce Type: cross Abstract: Sentiment analysis in software engineering focuses on understanding emotions expressed in software artifacts. Previous research highlighted the limita

researcharxiv-cs-ai

// Skill Learning for Autonomous Web Agents // Web agents can navigate a page, but ask them to repeat a checkout flow they already completed…

// Skill Learning for Autonomous Web Agents // Web agents can navigate a page, but ask them to repeat a checkout flow they already completed, and they start from scratch every time. This work introduc

agentsdair-ai--x

SpaceMind: A Modular and Self-Evolving Embodied Vision-Language Agent Framework for Autonomous On-orbit Servicing

arXiv:2604.14399v1 Announce Type: new Abstract: Autonomous on-orbit servicing demands embodied agents that perceive through visual sensors, reason about 3D spatial situations, and execute multi-phase

agentsarxiv-cs-ro

The Code Whisperer: LLM and Graph-Based AI for Smell and Vulnerability Resolution

arXiv:2604.13114v1 Announce Type: cross Abstract: Code smells and software vulnerabilities both increase maintenance cost, yet they are often handled by separate tools that miss structural context and

researcharxiv-cs-ai

'The post all LLMs hate and want you to NOT SEE' ^^ Serious title, you can also discuss this with the LLM, it would be biased against it, as…

'The post all LLMs hate and want you to NOT SEE' ^^ Serious title, you can also discuss this with the LLM, it would be biased against it, as it's known at this point that memory is the true long term

agentsharrison-chase--x

Hardware

Thermodynamic Diffusion Inference with Minimal Digital Conditioning

arXiv:2604.14332v1 Announce Type: new Abstract: Diffusion-model inference and overdamped Langevin dynamics are formally identical. A physical substrate that encodes the score function therefore equili

hardwarearxiv-cs-lg

TOPCELL: Topology Optimization of Standard Cell via LLMs

arXiv:2604.14237v1 Announce Type: new Abstract: Transistor topology optimization is a critical step in standard cell design, directly dictating diffusion sharing efficiency and downstream routability.

safetyarxiv-cs-lg

Towards Bridging the Reward-Generation Gap in Direct Alignment Algorithms

arXiv:2506.09457v3 Announce Type: replace Abstract: Direct Alignment Algorithms (DAAs), such as Direct Preference Optimization (DPO) and Simple Preference Optimization (SimPO), have emerged as efficie

safetyarxiv-cs-cl

Towards Scalable Lightweight GUI Agents via Multi-role Orchestration

arXiv:2604.13488v1 Announce Type: new Abstract: Autonomous Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) enable digital automation on end-user devices. Whil

safetyarxiv-cs-ai

Tug-of-War within A Decade: Conflict Resolution in Vulnerability Analysis via Teacher-Guided Retrieval-Augmented Generations

arXiv:2604.14172v1 Announce Type: new Abstract: Large Language Models (LLMs) are essential for analyzing and addressing vulnerabilities in cybersecurity. However, among over 200,000 vulnerabilities we

Universal hidden monotonic trend estimation with contrastive learning

arXiv:2210.09817v3 Announce Type: replace Abstract: In this paper, we describe a universal method for extracting the underlying monotonic trend factor from time series data. We propose an approach rel

v0.21.0-rc1

Ollama v0.21.0-rc1 is a pre-release that includes improvements to Gemma 4 Tool Calling, adds the latest models to the Ollama App, and fixes issues with launching the OpenClaw TUI. The release enables

local-aiollama-releases

XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts

arXiv:2604.05242v2 Announce Type: replace Abstract: Multi-bit watermarking has emerged as a promising solution for embedding imperceptible binary messages into Large Language Model (LLM)-generated tex

You gotta pump those numbers up. Those are rookie numbers in this racket.

tutorialsjeremy-howard--x

This appears to be a tweet by Jeremy Howard, a prominent figure in AI and machine learning, likely discussing the need to increase certain metrics or performance benchmarks in AI development or a rela

A deep mystery to me is that if I upload writing to a chatbot and ask it for a list of individual improvements, basically everything it give…

tutorialsjeremy-howard--x

A deep mystery to me is that if I upload writing to a chatbot and ask it for a list of individual improvements, basically everything it gives me makes the text more punchy and direct and nice to read.

A Function-Centric Perspective on Flat and Sharp Minima

arXiv:2510.12451v2 Announce Type: replace-cross Abstract: Flat minima are strongly associated with improved generalisation in deep neural networks. However, this connection has proven nuanced in recen

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems

arXiv:2603.25749v2 Announce Type: replace-cross Abstract: Arc-fault circuit interrupters (AFCIs) are essential for mitigating fire hazards in residential photovoltaic (PV) systems, yet achieving relia

local-aiarxiv-cs-lg

A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarios

arXiv:2512.23748v2 Announce Type: replace Abstract: For complex simulation problems, inferring parameters often precludes the use of classical likelihood-based techniques due to intractable likelihood

tutorialsarxiv-cs-lg

Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning

arXiv:2601.13115v2 Announce Type: replace Abstract: Large Language Models (LLMs) have become a popular interface for human-AI interaction, supporting information seeking and task assistance through na

agentsarxiv-cs-cl

AI for Materials Science starter kit [D]

researchr-machinelearning

This r/MachineLearning discussion post serves as a community-curated beginner's resource for applying artificial intelligence and machine learning to materials science, likely compiling recommended to

b8814

local-aillama-cpp-releases

llama.cpp is a C/C++ library for LLM inference that enables running large language models on consumer hardware. Release b8814 is a specific version in the project's continuous release cycle, which fol

Beyond Voxel 3D Editing: Learning from 3D Masks and Self-Constructed Data

arXiv:2604.13688v1 Announce Type: new Abstract: 3D editing refers to the ability to apply local or global modifications to 3D assets. Effective 3D editing requires maintaining semantic consistency by

local-aiarxiv-cs-cv

Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference

arXiv:2604.13634v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by letting draft tokens bypass full verification, but conventional frameworks suffer from fre