Search: “models”

The Chase Is the Curriculum, the Capture Anchors the Credit: Pursuit-Evasion Self-Play for Zero-Data LLM Reasoning

arXiv:2608.21871v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has become the dominant recipe for improving large language model reasoning, yet it presumes large human-

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

The Compaction Cliff in Long-Running AI Agent Memory

DGX agent

arXiv:2608.22752v1 Announce Type: new Abstract: A safety rule and an episodic log compete for the same tokens in an AI agent's context. When the budget overflows, both are summarized at the same rate;

model-releasesarxiv-cs-ai

25 Aug 2026

The Error of Deep Operator Networks Is the Sum of Its Parts: Branch-Trunk and Mode Error Decompositions

arXiv:2602.21910v2 Announce Type: replace Abstract: Operator learning has the potential to strongly impact scientific computing by learning solution operators for differential equations, potentially a

The Geometry of Low-Resource Language Representations

arXiv:2608.23358v1 Announce Type: new Abstract: The performance gap between low- and high-resource languages in LLMs is widely known, but it remains unclear which internal model factors drive these di

The Retriever Should Remember: Experience-Amortized Reranking for Long-Term Agent Memory

arXiv:2608.22767v1 Announce Type: new Abstract: Long-term language-model agents accumulate memories across interactions, but their retrievers typically do not accumulate retrieval experience. Semantic

The Setting of IMU Parameters in Kalman Filtering-based Information Fusion

model-releasesarxiv-cs-ro

arXiv:2608.21433v1 Announce Type: new Abstract: The setting or tuning of specifications for the inertial measurement unit (IMU) is tricky in sensor fusion. The underneath conundrum is caused by the fa

TO-Agents: A Multi-Agent AI Framework for Subjective Preference-Guided Topology Optimization

arXiv:2605.21622v2 Announce Type: replace Abstract: Topology optimization can generate efficient structures, but designers often must manually translate qualitative intent, such as desired visual styl

Safety

Towards Actionable Surgical Team Dynamics: from Teamwork to Counterfactual Annotations

arXiv:2608.23344v1 Announce Type: new Abstract: Modeling team interactions in high-stakes environments such as operating rooms is critical for understanding how coordination, communication, and indivi

safetyarxiv-cs-lg

Towards Comprehensive Basketball Understanding

arXiv:2608.23435v1 Announce Type: cross Abstract: Understanding a basketball game requires recognizing events, localizing actions, identifying players, and relating these to structured game knowledge.

TRACE: Temporal Retrieval with Anchored and Convergent Evidence for Long-Horizon Video Understanding

model-releasesarxiv-cs-cl

arXiv:2608.22516v1 Announce Type: cross Abstract: A long-video answer is evidence-supported only when the frames decoded from the video cover every event the answer depends on. Existing evaluations sc

Hardware

Tracing the Unlabeled Storm: Cross-Variable Transfer in a Lagrangian Atmospheric JEPA Framework

arXiv:2608.22358v1 Announce Type: new Abstract: Deep atmospheric convection governs South Asian monsoon variability, yet attempting to learn its latent world model directly from zero-inflated, heavy-t

hardwarearxiv-cs-lg

Training Proactive and Personalized LLM Agents

arXiv:2511.02208v2 Announce Type: replace Abstract: Despite rapid progress, current AI agents are primarily optimized for isolated task completion. We argue for a paradigm shift toward training agents

Vision Guided Target Conditioned Control for Autonomous Excavation

model-releasesarxiv-cs-ro

arXiv:2608.21778v1 Announce Type: new Abstract: Autonomous excavation requires an intelligent control system that can convert spatial work intent into coordinated bucket motion under contact-rich soil

Safety

Who Pays More for Safety? Measuring the Disparate Cost of Safety Alignment across Languages

arXiv:2608.22490v1 Announce Type: new Abstract: Safety alignment helps models adhere to human values, but it often reduces response utility. We ask a critical but understudied question: Does safety al

safetyarxiv-cs-cl

A Factorial Ablation of a Speech-to-SFT Pipeline: Differential Effects on Data Quality and Downstream Transfer

arXiv:2608.20394v1 Announce Type: cross Abstract: Industry pipelines that turn speech into supervised fine-tuning (SFT) data via multi-stage refinement are increasingly adopted but, to our knowledge,

applicationsarxiv-cs-cl

A Survey on Foundations and Frontiers of Multimodal Agentic Frameworks: Techniques and Applications

arXiv:2608.20379v1 Announce Type: new Abstract: Advances in large language models (LLMs) have fueled a wave of research into agency: the ability to reason, plan, and act. This effort has produced agen

AgentMercury: Your Agent Can Synthesize Verifiable Environments for Business Scenarios at scale

arXiv:2608.20634v1 Announce Type: cross Abstract: Agents learn to act through interaction with environments, yet the environments used for training are often manually constructed or synthesized around

Amortized Bandwidth Learning for Kernel Density Estimation under Logarithmic Score

arXiv:2608.20445v1 Announce Type: new Abstract: Kernel density estimation converts finite samples into probability densities, but its performance depends critically on bandwidth selection. Classical s

Anatomy-Informed Neural Networks: Encoding Anatomic Priors in Loss and Architecture, with an SE(3) Formulation of Guidewire-Induced Aortoiliac Deformation

arXiv:2608.21332v1 Announce Type: new Abstract: Deep-learning models of anatomy can be numerically plausible yet anatomically impossible, and they generalize poorly when data are scarce. We introduce

Anchored Regularized Direct Least Squares (ARDLS): Integrating Established Prioritization Operators for Priority Elicitation in the Analytic Hierarchy Process

arXiv:2608.21187v1 Announce Type: cross Abstract: Pairwise reciprocal matrices are fundamental to the Analytic Hierarchy Process (AHP), a decision-making model. While the Direct Least Squares (DLS) me

researcharxiv-cs-ai

AsmEvo: Agentic Assembly-Level Optimization of AMD GPU Kernels with Functional Equivalence Verification

model-releasesarxiv-cs-cl

arXiv:2608.20711v1 Announce Type: new Abstract: High-performance ML systems increasingly rely on GPU kernels whose editable source is unavailable, generated, or too distant from final machine code to

Auditable by Construction: An Ontology-Driven Framework for Trustworthy LLM Analytics in Enterprise Finance

arXiv:2608.20661v1 Announce Type: new Abstract: Enterprise adoption of large language models in finance is constrained less by fluency than by trust: in Financial Planning and Analysis (FP&A) and othe

applicationsarxiv-cs-ai

Beyond Prompt Engineering: A Systematic Analysis of Prompt Lexical Sensitivity and Its Impacts on Quality

arXiv:2608.20349v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit extreme sensitivity to surface-level prompt variations, in which minor lexical changes can trigger disproportiona

Capturing Cardiac Cyclicity through Phase-Equivariant Self-Supervised Learning

arXiv:2608.21147v1 Announce Type: new Abstract: The cyclic structure of physiological processes offers a natural prior for self-supervised representation learning, and the cardiac cycle provides a par

Local Ai

DAOP: Data-Aware Offloading and Predictive Pre-Calculation for Efficient MoE Inference

arXiv:2501.10375v3 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models, though highly effective for various machine learning tasks, face significant deployment challenges on memory-

local-aiarxiv-cs-lg

Hardware

Deterministic and probabilistic neural surrogates of global hybrid-Vlasov simulations

arXiv:2601.12614v4 Announce Type: replace-cross Abstract: Hybrid-Vlasov simulations resolve ion-kinetic effects in the solar wind-magnetosphere interaction, but even 5D (2D + 3V) configurations are co

hardwarearxiv-cs-lg

DiGS-Avatar: Single-Image Animatable 3D Human Reconstruction via UV-Space Diffusion

arXiv:2608.20759v1 Announce Type: new Abstract: Single-image 3D human reconstruction often suffers from over-smoothed textures and geometric inconsistencies. While diffusion models improve generative

researcharxiv-cs-cv

DreamBench-SWE: A Multi-Session Memory-Hygiene Benchmark for Software Agents

arXiv:2608.20664v1 Announce Type: new Abstract: DreamBench-SWE is a multi-session benchmark for software-agent memory hygiene in which later software tasks depend on non-inferable evidence from earlie

Safety

Driving with DINO: Vision Foundation Features as a Unified Bridge for Sim-to-Real Generation in Autonomous Driving

arXiv:2602.06159v3 Announce Type: replace Abstract: Driven by the emergence of Controllable Video Diffusion, existing Sim2Real methods for autonomous driving video generation typically rely on explici

safetyarxiv-cs-cv

EditPPT: Faithful Long-Deck Slide Editing via Structured Tool-Using Multi-Agent with Dual-Modal Validators

arXiv:2608.20381v1 Announce Type: cross Abstract: Automating slide editing requires simultaneously satisfying modification accuracy, preservation fidelity, and robustness to deck length. Existing LLM-

Extractive Summarization for Arabic Documents Using SAraBERT with a Semantic Siamese Similarity Evaluation Metric

arXiv:2608.20964v1 Announce Type: cross Abstract: In this research, we introduce SAraBERT, an enhanced version of AraBERT which proposes inter-sentence transformer layers for extractive summarization

researcharxiv-cs-ai

Fine-Grain GPU Parallelization of the Generalized Partition Crossover for Large-Scale Traveling Salesman Problems

arXiv:2608.21233v1 Announce Type: new Abstract: The Traveling Salesman Problem (TSP) is one of the most extensively studied NP-hard optimization problems. Genetic Algorithm (GA)-based solvers, such as

FlatLand: Personalized Graph Federated Learning via Tailored Lorentz Space

arXiv:2608.21096v1 Announce Type: new Abstract: Federated learning enables privacy-preserving collaborative training, but highly heterogeneous client data remain challenging, especially in graph feder

Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence

arXiv:2608.21156v1 Announce Type: cross Abstract: LLMs have evolved from language generators to autonomous agents capable of complex, long-horizon tasks. This evolution has produced paradigms includin

GroupSegment-SHAP: Shapley Value Explanations with Group-Segment Players for Multivariate Time Series

arXiv:2601.06114v2 Announce Type: replace-cross Abstract: Multivariate time-series models achieve strong predictive performance in healthcare, industry, energy, and finance, but how they combine cross

applicationsarxiv-cs-ai

GS-Net: Heterogeneous Vehicle Data Reuse via Generalizable Plug-and-Play 3DGS Module

model-releasesarxiv-cs-cv

arXiv:2409.11307v2 Announce Type: replace Abstract: End-to-end autonomous driving is increasingly data-driven, yet data reuse across vehicles remains limited. Each new vehicle often requires additiona

Infinite-dimensional generative diffusions via Doob's h-transform

arXiv:2602.06621v2 Announce Type: replace-cross Abstract: This paper introduces a rigorous framework for defining generative diffusion models in infinite dimensions via Doob's h-transform. Rather than

researcharxiv-cs-lg

Local Ai

Infrared Hotspot-Guided Early Warning of Lithium-Ion Battery Thermal Runaway Under Mechanical Abuse

arXiv:2608.20383v1 Announce Type: cross Abstract: Mechanical abuse can trigger thermal runaway (TR) in lithium-ion batteries through localized heat generation before sensor signals become decisive. Th

local-aiarxiv-cs-ai

JuryProbe: An Empirical Consensus-Risk Diagnostic for Routing Reference-Free Factuality Judge Panels to Grounded Verification

arXiv:2608.20607v1 Announce Type: cross Abstract: Panels of inexpensive LLM judges increasingly make accept-or-escalate decisions. In factuality settings, accepting a claim because several reference-f

Lightweight Adaptive ReduNet via Hyperspherical Manifold Learning

arXiv:2608.20668v1 Announce Type: cross Abstract: In recent years, a white-box neural network called ReduNet has been proposed, which employs the maximal coding rate reduction (MCR^2) principle to tra

LTR-ICD: A Ranking-Aware Framework for Automatic ICD Coding

arXiv:2510.13922v2 Announce Type: replace-cross Abstract: Clinical notes contain unstructured text provided by clinicians during patient encounters. These notes are usually accompanied by a sequence o

Maximum Entropy Encoding of Energy-Weighted Spherical Moments

model-releasesarxiv-cs-cv

arXiv:2608.20429v1 Announce Type: cross Abstract: We study how angular energy signals composed of non-negative Monte Carlo path samples can be compressed and reconstructed for irradiance using finite

Memory Augmentation Unlocks Efficient Chain-of-Thought Reasoning

arXiv:2608.21265v1 Announce Type: new Abstract: Large language models often rely on Chain-of-Thought (CoT) reasoning to solve complex tasks, but verbose reasoning traces introduce substantial inferenc

Local Ai

NeSAM: Neuro-Symbolic Kinodynamics with Soil Adaptation for Off-Road Mobility

arXiv:2608.21330v1 Announce Type: new Abstract: Accurate prediction of off-road vehicle motion over deformable terrain remains challenging because sinkage, slip, and traction vary with local soil cond

local-aiarxiv-cs-ro

NeuroStrata: An Electroencephalographic Connectivity-Aware Deep Representation Learning Framework for Dynamic Brain Network Analysis of Mental Stress

arXiv:2608.20354v1 Announce Type: cross Abstract: This study introduces NeuroStrata, a connectivity-aware deep representation learning framework for EEG-based mental stress analysis using Time-Varying

researcharxiv-cs-ai

Tutorials

OccluRank: Controllable Occlusion-Aware Layout-to-Image Generation by Adding Just an Ordinal Rank

arXiv:2608.20932v1 Announce Type: new Abstract: Layout-to-image generation enables explicit spatial control through bounding-box layouts, yet bounding boxes specify only instance locations and cannot

tutorialsarxiv-cs-cv

Primal Acceleration of Newton's Method

arXiv:2608.21359v1 Announce Type: cross Abstract: We develop a new direct accelerated Newton method for minimizing convex functions with Lipschitz continuous Hessian. The algorithm uses only primal va

Profiling What Matters: Context-Aware Item Profiles from Large-Scale Metadata for LLM Recommenders

arXiv:2608.20801v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have significantly advanced reranking in recommendation, effectively leveraging item-side information remains chall

applicationsarxiv-cs-ai