Search: “models”

Counting Without Numbers and Finding Without Words

arXiv:2603.24470v2 Announce Type: replace-cross Abstract: Every year, 10 million pets enter shelters, separated from their families. Despite desperate searches by both guardians and lost animals, 70%

Deep Learning for Subspace Regression

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arXiv:2509.23249v4 Announce Type: replace Abstract: It is often possible to perform reduced order modelling by specifying linear subspace which accurately captures the dynamics of the system. This app

researcharxiv-cs-lg

17 Apr 2026

Dense Neural Networks are not Universal Approximators

arXiv:2602.07618v3 Announce Type: replace Abstract: We investigate the approximation capabilities of dense neural networks. While universal approximation theorems establish that sufficiently large arc

Tutorials

DiscoTrace: Representing and Comparing Answering Strategies of Humans and LLMs in Information-Seeking Question Answering

arXiv:2604.15140v1 Announce Type: new Abstract: We introduce DiscoTrace, a method to identify the rhetorical strategies that answerers use when responding to information-seeking questions. DiscoTrace

tutorialsarxiv-cs-cl

Do Not Step Into the Same River Twice: Learning to Reason from Trial and Error

arXiv:2510.26109v4 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly boosted the reasoning capability of language models (LMs). However, existing

Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories

arXiv:2603.25903v2 Announce Type: replace Abstract: Scaling robot learning to long-horizon tasks remains a formidable challenge. While end-to-end policies often lack the structural priors needed for e

safetyarxiv-cs-ro

Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design

arXiv:2512.24120v2 Announce Type: replace Abstract: Automated neural network architecture design remains a significant challenge in computer vision. Task diversity and computational constraints requir

Enhancing LLM-based Search Agents via Contribution Weighted Group Relative Policy Optimization

arXiv:2604.14267v1 Announce Type: new Abstract: Search agents extend Large Language Models (LLMs) beyond static parametric knowledge by enabling access to up-to-date and long-tail information unavaila

Expressivity of Transformers: A Tropical Geometry Perspective

arXiv:2604.14727v1 Announce Type: new Abstract: To quantify the geometric expressivity of transformers, we introduce a tropical geometry framework to characterize their exact spatial partitioning capa

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

Tutorials

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

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

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

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

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

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

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

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

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.

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

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

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

Local Ai

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

Tutorials

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

Local Ai

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

Creo: From One-Shot Image Generation to Progressive, Co-Creative Ideation

arXiv:2604.13956v1 Announce Type: cross Abstract: Text-to-image (T2I) systems enable rapid generation of high-fidelity imagery but are misaligned with how visual ideas develop. T2I systems generate ou