Search: “papers”

arXiv:2505.24665v2 Announce Type: replace Abstract: Real world data often lie on low-dimensional Riemannian manifolds embedded in high-dimensional spaces. This motivates learning degenerate normalizin

applicationsarxiv-cs-lg

Agents

Learning to Assist: Physics-Grounded Human-Human Control via Multi-Agent Reinforcement Learning

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DGX agent

arXiv:2603.11346v2 Announce Type: replace Abstract: Humanoid robotics has strong potential to transform daily service and caregiving applications. Although recent advances in general motion tracking w

agentsarxiv-cs-cv

14 Apr 2026

Learning to Test: Physics-Informed Representation for Dynamical Instability Detection

arXiv:2604.10967v1 Announce Type: new Abstract: Many safety-critical scientific and engineering systems evolve according to differential-algebraic equations (DAEs), where dynamical behavior is constra

safetyarxiv-cs-lg

Linear Programming for Multi-Criteria Assessment with Cardinal and Ordinal Data: A Pessimistic Virtual Gap Analysis

arXiv:2604.09555v1 Announce Type: new Abstract: Multi-criteria Analysis (MCA) is used to rank alternatives based on various criteria. Key MCA methods, such as Multiple Criteria Decision Making (MCDM)

LPNSR: Optimal Noise-Guided Diffusion Image Super-Resolution Via Learnable Noise Prediction

arXiv:2603.21045v4 Announce Type: replace-cross Abstract: Diffusion-based image super-resolution (SR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) observations, yet faces a

Lung Cancer Detection Using Deep Learning

arXiv:2604.10765v1 Announce Type: cross Abstract: Lung cancer, the second leading cause of cancer-related deaths, is primarily linked to long-term tobacco smoking (85% of cases). Surprisingly, 10-15%

MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis

arXiv:2604.11188v1 Announce Type: cross Abstract: Synthesizing high-quality mathematical reasoning data without human priors remains a significant challenge. Current approaches typically rely on seed

MAVEN-T: Multi-Agent enVironment-aware Enhanced Neural Trajectory predictor with Reinforcement Learning

arXiv:2604.10169v1 Announce Type: new Abstract: Trajectory prediction remains a critical yet challenging component in autonomous driving systems, requiring sophisticated reasoning capabilities while m

Measuring What Matters!! Assessing Therapeutic Principles in Mental-Health Conversation

model-releasesarxiv-cs-cl

arXiv:2604.05795v2 Announce Type: replace Abstract: The increasing use of large language models in mental health applications calls for principled evaluation frameworks that assess alignment with psyc

Minimizing classical resources in variational measurement-based quantum computation for generative modeling

arXiv:2604.11578v1 Announce Type: cross Abstract: Measurement-based quantum computation (MBQC) is a framework for quantum information processing in which a computational task is carried out through on

Mining Attribute Subspaces for Efficient Fine-tuning of 3D Foundation Models

arXiv:2604.10095v1 Announce Type: new Abstract: With the emergence of 3D foundation models, there is growing interest in fine-tuning them for downstream tasks, where LoRA is the dominant fine-tuning p

researcharxiv-cs-cv

MIXAR: Scaling Autoregressive Pixel-based Language Models to Multiple Languages and Scripts

arXiv:2604.11575v1 Announce Type: new Abstract: Pixel-based language models are gaining momentum as alternatives to traditional token-based approaches, promising to circumvent tokenization challenges.

researcharxiv-cs-cl

MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets

arXiv:2308.12067v3 Announce Type: replace-cross Abstract: Multimodal large language models are typically trained in two stages: first pre-training on image-text pairs, and then fine-tuning using super

Mobile GUI Agent Privacy Personalization with Trajectory Induced Preference Optimization

arXiv:2604.11259v1 Announce Type: new Abstract: Mobile GUI agents powered by Multimodal Large Language Models (MLLMs) can execute complex tasks on mobile devices. Despite this progress, most existing

MoEITS: A Green AI approach for simplifying MoE-LLMs

arXiv:2604.10603v1 Announce Type: cross Abstract: Large language models are transforming all areas of academia and industry, attracting the attention of researchers, professionals, and the general pub

Most AI assistants wait for you to ask. But a truly useful agent should notice you need help before you say anything. New research takes a s…

Most AI assistants wait for you to ask. But a truly useful agent should notice you need help before you say anything. New research takes a serious shot at building proactive agents that work in real t

model-releasesdair-ai--x

Multi-Granularity Reasoning for Image Quality Assessment via Attribute-Aware Reinforcement Learning to Rank

arXiv:2604.09704v1 Announce Type: new Abstract: Recent advances in reasoning-induced image quality assessment (IQA) have demonstrated the power of reinforcement learning to rank (RL2R) for training vi

safetyarxiv-cs-cv

Multi-Modal Learning meets Genetic Programming: Analyzing Alignment in Latent Space Optimization

arXiv:2604.08324v2 Announce Type: replace-cross Abstract: Symbolic regression (SR) aims to discover mathematical expressions from data, a task traditionally tackled using Genetic Programming (GP) thro

Multi-modal, multi-scale representation learning for satellite imagery analysis just needs a good ALiBi

model-releasesarxiv-cs-cv

arXiv:2604.10347v1 Announce Type: new Abstract: Vision foundation models have been shown to be effective at processing satellite imagery into representations fit for downstream tasks, however, creatin

Multinex: Lightweight Low-light Image Enhancement via Multi-prior Retinex

arXiv:2604.10359v1 Announce Type: cross Abstract: Low-light image enhancement (LLIE) aims to restore natural visibility, color fidelity, and structural detail under severe illumination degradation. St

Network Effects and Agreement Drift in LLM Debates

arXiv:2604.11312v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated an unprecedented ability to simulate human-like social behaviors, making them useful tools for simulati

Neural Generalized Mixed-Effects Models

model-releasesarxiv-cs-lg

arXiv:2604.10976v1 Announce Type: cross Abstract: Generalized linear mixed-effects models (GLMMs) are widely used to analyze grouped and hierarchical data. In a GLMM, each response is assumed to follo

Agents

Neuro-Symbolic Strong-AI Robots with Closed Knowledge Assumption: Learning and Deductions

arXiv:2604.09567v1 Announce Type: cross Abstract: Knowledge representation formalisms are aimed to represent general conceptual information and are typically used in the construction of the knowledge

agentsarxiv-cs-ai

Applications

Non-stationary Diffusion For Probabilistic Time Series Forecasting

arXiv:2505.04278v3 Announce Type: replace-cross Abstract: Due to the dynamics of underlying physics and external influences, the uncertainty of time series often varies over time. However, existing De

applicationsarxiv-cs-ai

OmniScript: Towards Audio-Visual Script Generation for Long-Form Cinematic Video

model-releasesarxiv-cs-cv

arXiv:2604.11102v1 Announce Type: new Abstract: Current multimodal large language models (MLLMs) have demonstrated remarkable capabilities in short-form video understanding, yet translating long-form

On the Convergence of Gradient Descent on Learning Transformers with Residual Connections

arXiv:2506.05249v4 Announce Type: replace Abstract: Transformer models have emerged as fundamental tools across various scientific and engineering disciplines, owing to their outstanding performance i

researcharxiv-cs-lg

Online Covariance Matrix Estimation in Sketched Newton Methods

model-releasesarxiv-cs-lg

arXiv:2502.07114v2 Announce Type: replace-cross Abstract: Given the ubiquity of streaming data, online algorithms have been widely used for parameter estimation, with second-order methods particularly

OOM-RL: Out-of-Money Reinforcement Learning Market-Driven Alignment for LLM-Based Multi-Agent Systems

arXiv:2604.11477v1 Announce Type: new Abstract: The alignment of Multi-Agent Systems (MAS) for autonomous software engineering is constrained by evaluator epistemic uncertainty. Current paradigms, suc

Optimal Stability of KL Divergence under Gaussian Perturbations

arXiv:2604.11026v1 Announce Type: cross Abstract: We study the problem of characterizing the stability of Kullback-Leibler (KL) divergence under Gaussian perturbations beyond Gaussian families. Existi

Local Ai

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights

arXiv:2504.06307v2 Announce Type: replace-cross Abstract: The rapid adoption of large language models (LLMs) has led to significant energy consumption and carbon emissions, posing a critical challenge

local-aiarxiv-cs-ai

PAC learning PDFA from data streams

arXiv:2604.02244v3 Announce Type: replace-cross Abstract: This is an extended version of our publication Learning state machines from data streams: A generic strategy and an improved heuristic, Intern

researcharxiv-cs-lg

Local Ai

Pair2Scene: Learning Local Object Relations for Procedural Scene Generation

arXiv:2604.11808v1 Announce Type: new Abstract: Generating high-fidelity 3D indoor scenes remains a significant challenge due to data scarcity and the complexity of modeling intricate spatial relation

local-aiarxiv-cs-cv

Para-B&B: Load-Balanced Deterministic Parallelization of Solving MIP

arXiv:2604.09556v1 Announce Type: cross Abstract: Mixed-integer programming (MIP) extends linear programming by incorporating both continuous and integer decision variables, making it widely used in p

ParseBench is the most comprehensive OCR benchmark for real-world enterprise documents: financial filings, contracts, insurance documents, a…

model-releasesjerry-liu--x

ParseBench is the most comprehensive OCR benchmark for real-world enterprise documents: financial filings, contracts, insurance documents, and more. We evaluate across 5 dimensions that are present am

PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding

arXiv:2412.11390v3 Announce Type: replace-cross Abstract: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the brain and external devices. Howeve

safetyarxiv-cs-lg

Physical Commonsense Reasoning for Lower-Resourced Languages and Dialects: a Study on Basque

arXiv:2602.14812v3 Announce Type: replace Abstract: Physical commonsense reasoning represents a fundamental capability of human intelligence, enabling individuals to understand their environment, pred

researcharxiv-cs-cl

Poisoning with A Pill: Circumventing Detection in Federated Learning

arXiv:2407.15389v2 Announce Type: replace Abstract: Without direct access to the client's data, federated learning (FL) is well-known for its unique strength in data privacy protection among existing

researcharxiv-cs-lg

PokeRL: Reinforcement Learning for Pokemon Red

model-releasesarxiv-cs-lg

arXiv:2604.10812v1 Announce Type: new Abstract: Pokemon Red is a long-horizon JRPG with sparse rewards, partial observability, and quirky control mechanics that make it a challenging benchmark for rei

Agents

PoTable: Towards Systematic Thinking via Plan-then-Execute Stage Reasoning on Tables

arXiv:2412.04272v5 Announce Type: replace-cross Abstract: In recent years, table reasoning has garnered substantial research interest, particularly regarding its integration with Large Language Models

agentsarxiv-cs-ai

Preference-Agile Multi-Objective Optimization for Real-time Vehicle Dispatching

arXiv:2604.10664v1 Announce Type: new Abstract: Multi-objective optimization (MOO) has been widely studied in literature because of its versatility in human-centered decision making in real-life appli

Principles Do Not Apply Themselves: A Hermeneutic Perspective on AI Alignment

arXiv:2604.10673v1 Announce Type: new Abstract: AI alignment is often framed as the task of ensuring that an AI system follows a set of stated principles or human preferences, but general principles r

Progressive Multimodal Interaction Network for Reliable Quantification of Fish Feeding Intensity in Aquaculture

arXiv:2506.14170v3 Announce Type: replace-cross Abstract: Accurate quantification of fish feeding intensity is crucial for precision feeding in aquaculture, as it directly affects feed utilization and

Progressively Texture-Aware Diffusion for Contrast-Enhanced Sparse-View CT

arXiv:2604.11559v1 Announce Type: new Abstract: Diffusion-based sparse-view CT (SVCT) imaging has achieved remarkable advancements in recent years, thanks to its more stable generative capability. How

researcharxiv-cs-cv

Local Ai

{Psi}-Map: Panoptic Surface Integrated Mapping Enables Real2Sim Transfer

arXiv:2604.10982v1 Announce Type: new Abstract: Open-vocabulary panoptic reconstruction is essential for advanced robotics perception and simulation. However, existing methods based on 3D Gaussian Spl

local-aiarxiv-cs-ro

Applications

Quantization Robustness to Input Degradations for Object Detection

arXiv:2508.19600v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is crucial for deploying efficient object detection models, like YOLO, on resource-constrained devices. However, th

applicationsarxiv-cs-cv

R2E-VID: Two-Stage Robust Routing via Temporal Gating for Elastic Edge-Cloud Video Inference

arXiv:2604.09681v1 Announce Type: cross Abstract: With the rapid growth of large-scale video analytics applications, edge-cloud collaborative systems have become the dominant paradigm for real-time in

researcharxiv-cs-cv

Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty

arXiv:2604.10072v1 Announce Type: new Abstract: Recent advancements in the Generative Reward Model (GRM) have demonstrated its potential to enhance the reasoning abilities of LLMs through Chain-of-Tho

researcharxiv-cs-cl

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