Search: “evaluation”

Q-Regularized Generative Auto-Bidding: From Suboptimal Trajectories to Optimal Policies

arXiv:2601.02754v3 Announce Type: replace-cross Abstract: With the rapid development of e-commerce, auto-bidding has become a key asset in optimizing advertising performance under diverse advertiser e

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QuantumPhaseNet: A Gauge-Covariant Geometric and Quantum-Spectral Theory of Semantic Concept Hierarchies with Prototype Validation of a Classical Quantum-Inspired Model

DGX agent

arXiv:2608.15820v1 Announce Type: new Abstract: We present QuantumPhaseNet, a gauge-covariant geometric and quantum-spectral extension of Transformer representations. Context-dependent semantic states

safetyarxiv-cs-cl

18 Aug 2026

R^3-Bench: LLMs Struggle with Resource-Rational Reasoning under Shared Budgets

arXiv:2608.16033v1 Announce Type: new Abstract: In cognitive science, resource rationality asks how an agent should allocate limited computation to maximize expected value. Most reasoning and agent be

safetyarxiv-cs-cl

Local Ai

RadioVIL: Anomaly-Aware Diffusion Models for Radio Map Inpainting and Zero-Shot Vehicle Localization

arXiv:2608.16167v1 Announce Type: cross Abstract: High-precision radio map construction is essential for emerging 6G Integrated Sensing and Communication (ISAC) applications, including digital twins a

local-aiarxiv-cs-lg

RAIN-FIT: Learning of Fitting Surfaces and Noise Distribution from Large Data Sets

arXiv:2604.03491v2 Announce Type: replace-cross Abstract: This paper proposes a method for estimating a surface that contains a given set of points from noisy measurements. More precisely, by assuming

Agents

ReasonCast: Agentic Demand Forecasting with Selective Semantic Reasoning

arXiv:2608.15291v1 Announce Type: new Abstract: Demand forecasting increasingly requires combining two complementary sources of information: historical sales reveal recurring numerical dynamics, while

agentsarxiv-cs-ai

ReForge: Keeping ABR Algorithms Never Finished with Verified Large Language Model Edits

arXiv:2608.15138v1 Announce Type: new Abstract: Designing an ABR algorithm for one network scenario takes an engineer months, and large language models now do this work in hours, matching or beating h

Registration-Free Hyperspectral Reconstruction from RGB via a Permutation-Invariant Gram-Matrix Principle

arXiv:2608.14994v1 Announce Type: new Abstract: Reconstructing a spatially and spectrally high-resolution hyperspectral image (HR-HSI) from a low-resolution HSI (LR-HSI) and a high-resolution RGB imag

ReliaGate: Reliability Routing for Low-Stakes Wearable Stress Prediction

arXiv:2608.15951v1 Announce Type: new Abstract: We study when a wearable stress system should surface a prediction rather than change it. In low-stakes reflection and summary settings, aggregate accur

researcharxiv-cs-lg

Remember Smarter: Visual History Compressor and Hyperbolic Experience Space for Robotic Memory

arXiv:2608.15269v1 Announce Type: new Abstract: Long-horizon robot policies require compact access to recent observations and reusable experience without expanding the vision-language-action (VLA) con

researcharxiv-cs-ro

Remote-Sensing City Layout Extraction with MLLM

arXiv:2608.16484v1 Announce Type: new Abstract: Remote-sensing systems usually describe urban content with detection boxes, semantic masks, or vector boundaries. Such outputs locate classes and suppor

ReRef-3D: A Benchmark for Spatial Referring Expression-Guided 3D Scene Rearrangement

model-releasesarxiv-cs-cl

arXiv:2608.16011v1 Announce Type: new Abstract: We introduce ReRef-3D, a benchmark for language-guided placement in 3D scenes. It contains 33,826 instructions across 998 CLEVR-derived scenes, spanning

Reward hacking in physical reinforcement learning revealed by turbulent drag reduction

arXiv:2606.06227v3 Announce Type: replace-cross Abstract: Reinforcement-learning controllers optimise specified rewards, but in physical systems those rewards often capture only part of the true contr

RLCascadeRouter: Quality-Estimator-Free Cascade Routing via Reinforcement Learning

arXiv:2608.15817v1 Announce Type: new Abstract: The growing ecosystem of large language models (LLMs) offers huge potential to optimize performance-cost trade-offs. However, their heterogeneous capabi

Robot-Body-Aware Traversal Risk Graph Planning for Wheeled-Legged Robots in Complex Terrain

model-releasesarxiv-cs-ro

arXiv:2608.16433v1 Announce Type: new Abstract: Traversal Risk Graphs (TRGs) provide a compact, terrain-aware representation for global navigation, but native TRG costs are computed over circular node

Robust structure from motion for aerial-ground images via detector-free feature matching and multi-view track refinement

arXiv:2608.15251v1 Announce Type: new Abstract: Integrated 3D reconstruction from aerial-ground images is essential for generating high-precision urban 3D models, yet severe variations in viewpoint, s

safetyarxiv-cs-cv

RoofGS: Roofline-Guided End-to-End Acceleration of 3D Gaussian Splatting

arXiv:2608.15785v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables real-time novel-view synthesis but remains limited on GPUs at high resolutions. Through a stage-wise Roofline chara

S^3: A Smooth Simulation Surrogate for Optimizing Discrete Abstractions of Dynamical Systems

arXiv:2608.15920v1 Announce Type: cross Abstract: Intelligent systems are increasingly deployed in safety-critical settings with black-box controllers, including neural networks. The properties and be

SAPE: Sandwich Adapters for Parameter Efficiency in Large Language Model Fine-Tuning

arXiv:2608.15360v1 Announce Type: cross Abstract: While Parameter-Efficient Fine-Tuning (PEFT) has substantially reduced the hardware cost of adapting Large Language Models (LLMs) by decreasing the nu

SAUL: Sharpness-Aware Augmented-Lagrangian Unlearning

arXiv:2608.16249v1 Announce Type: new Abstract: Machine unlearning in Large Language Models (LLMs) faces a critical trade-off between erasing target knowledge and preserving general utility. We propos

Scale-Consistent Posterior Dynamics for Diffusion Inverse Problems

arXiv:2608.15144v1 Announce Type: cross Abstract: Posterior sampling with a pretrained diffusion prior is governed by a conditional score whose intermediate likelihood component is generally intractab

SchurQuant: Groupwise Discrete Optimization for Layer-Wise LLM Quantization

arXiv:2608.15567v1 Announce Type: new Abstract: Weight-only post-training quantization (PTQ) enables the deployment of large language models under tight memory budgets, but accuracy often collapses at

SCOUT: Semantic Concept Discovery for Open-Vocabulary Editing of face Recognition Templates

arXiv:2608.16251v1 Announce Type: new Abstract: Face recognition templates are compact identity representations, yet they also encode rich semantic information about facial appearance. Prior work has

Seeing the Bigger Picture: 3D Latent Mapping for Mobile Manipulation Policy Learning

arXiv:2510.03885v4 Announce Type: replace Abstract: In this paper, we demonstrate that mobile manipulation policies utilizing a 3D latent map achieve stronger spatial and temporal reasoning than polic

safetyarxiv-cs-ro

Self-Supervised Auxiliary Task Discovery for Stable Reinforcement Learning in Stock Trading

arXiv:2608.15841v1 Announce Type: new Abstract: Reinforcement learning has gained increasing attention as a data-driven approach for stock trading. However, learning a policy that is both profitable a

Sequential Multimodal Evidence Optimization for Product Media Ranking in E-Commerce

arXiv:2608.15662v1 Announce Type: new Abstract: On modern e-commerce stores, customers consume ordered slates of heterogeneous product media, such as images, videos, and 3D renders, before making purc

Shape Operator PCA: Curvature-Aware Projections for Geometric Machine Learning

arXiv:2608.15313v1 Announce Type: cross Abstract: In this paper, we propose SHOPCA (Shape Operator-based Principal Component Analysis), a novel method for unsupervised metric learning and dimensionali

SingDance: Compositional Zero-Shot Singing-and-Dancing Video Generation with Role-Aware Audio Conditioning

arXiv:2608.16220v1 Announce Type: cross Abstract: Generating personalized dance videos from a reference image, text prompt, and audio track requires music-conditioned body motion. Singing-and-dancing

safetyarxiv-cs-cv

SKILL: Self-correcting Knowledge-guided Iterative Large Language Model Agent for Logic Optimization

arXiv:2608.14579v1 Announce Type: new Abstract: Logic synthesis optimization poses significant challenges due to exponentially growing search spaces, sparse reward signals, and diverse logic structure

Local Ai

SL-S4Wave: Self-Supervised Learning of Physiological Waveforms with Structured State Space Models

arXiv:2606.19888v2 Announce Type: replace-cross Abstract: Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant challenges due to high sampling rates, mu

local-aiarxiv-cs-ai

SMOPD: Selective Token-Entropy Masking for Dirty-History Multi-Turn On-Policy Self-Distillation

arXiv:2608.14647v1 Announce Type: cross Abstract: Dirty-history rollouts make multi-turn on-policy self-distillation (OPSD) brittle: once a student emits an erroneous intermediate reply, later turns a

SOS! : A Streamlined Object-Conditional Transformer for Model-free Segmentation

arXiv:2608.15295v1 Announce Type: new Abstract: Foundation segmentation models excel at generating high-quality, class-agnostic masks, but they struggle to associate these proposals with specific targ

SparkVLA: Stop-Aware Hierarchical VLA with Adaptive Action Chunking for Long-Horizon Manipulation

arXiv:2608.16172v1 Announce Type: new Abstract: At every re-observation point in a hierarchical Vision-Language-Action (VLA) system, two interface decisions must be made: when to terminate the current

researcharxiv-cs-ro

Agents

Spatial Attention Noise Masking for Causally Sufficient Interpretability

arXiv:2608.14725v1 Announce Type: new Abstract: We present a novel causal approach to interpretability for computer vision models that dynamically masks the input image prior to classification. The in

agentsarxiv-cs-cv

Spectral Rank Certification for Foundation Model Adapters

arXiv:2608.15351v1 Announce Type: new Abstract: Nominal LoRA rank is a design parameter; calibrated spectral evidence is a separate inferential quantity. This article develops a finite-sample framewor

SQuad: Sub-Quadratic Attention Distillation for Efficient Video Generation

arXiv:2608.16585v1 Announce Type: new Abstract: Video Diffusion Transformers (DiTs) spend most of their compute inside the Self-Attention operation, whose cost grows quadratically, O(n^2), with the nu

STAGE: Controlled Objective Admission for Multi-Preference LLM Alignment

model-releasesarxiv-cs-cl

arXiv:2608.16553v1 Announce Type: new Abstract: Multi-preference alignment is often framed as scalarization: combine reward dimensions, then optimize. This leaves a temporal decision underspecified: w

STAR-FL: Secure Federated Learning with Spatial-Temporal Analysis and Robust Aggregation

arXiv:2608.14861v1 Announce Type: cross Abstract: Data poisoning attacks pose serious security threats to Federated Learning (FL) systems in Computer Vision. Despite growing research attention, two ke

Static Pruning Across Sparse Retrieval Regimes: What Transfers, What Breaks, and What Still Helps

arXiv:2608.16309v1 Announce Type: cross Abstract: Static pruning is widely used to accelerate sparse neural retrieval, yet existing studies each validate their conclusions within a single custom pipel

researcharxiv-cs-ai

Sterilizable Scene Graph Generation for Operating Rooms

model-releasesarxiv-cs-cv

arXiv:2608.16469v1 Announce Type: new Abstract: Scene graph generation from surgical video enables a holistic and structured understanding of surgical scenes by modeling objects and their semantic rel

Structured Prediction for Scalable Spreadsheet Table Understanding: From Cell Types to Table Ranges (Extended Version)

arXiv:2608.16050v1 Announce Type: cross Abstract: Spreadsheets are a primary medium for publishing tabular data, yet automatically extracting structured content from them remains difficult due to hete

Tutorials

Supervising the Path to Fine Scales: GalerkinFlow for Scientific-Field and Image Super-Resolution

arXiv:2608.16546v1 Announce Type: new Abstract: Most super-resolution models learn from paired data by supervising only the final high-resolution output. This provides little control over how the pred

tutorialsarxiv-cs-cv

SurgVIL: Scaling Surgical Robot Imitation Learning with Open-source Surgical Videos

arXiv:2608.16058v1 Announce Type: new Abstract: Learning-based surgical robot autonomy requires large-scale demonstrations with synchronized videos and robot actions, but such data are exceedingly rar

safetyarxiv-cs-ro

Synthesizing Post-Acetazolamide Cerebral Blood Flow Maps from Baseline MRI in Moyamoya Using 3D Generative AI

arXiv:2608.14758v1 Announce Type: cross Abstract: For patients with Moyamoya disease, impaired cerebrovascular reserve (CVR) is an important hemodynamic criterion for recommending extracranial-to-intr

Synthetic Data Augmentation for Satellite-Based Analysis of Battle-Damaged Agricultural Fields in Ukraine

arXiv:2608.16380v1 Announce Type: cross Abstract: Monitoring war-induced damage to agricultural land in Ukraine is important for understanding threats to food security, environmental stability, and po

researcharxiv-cs-ai

Synthetic Image Detection with CLIP: Understanding and Assessing Predictive Cues

model-releasesarxiv-cs-cv

arXiv:2602.12381v2 Announce Type: replace Abstract: Recent generative models produce near-photorealistic images, challenging the trustworthiness of photographs. Synthetic image detection (SID) methods

TAHB: A Comprehensive Benchmark for Text-Attributed Hypergraph Learning

arXiv:2608.15055v1 Announce Type: new Abstract: Hypergraphs effectively model higher-order groupwise relationships beyond pairwise interactions, while pretrained language models (PLMs) and large langu

Task-Driven Three-Layer Distributed Scheduling for Emergency Earth Observation in Large Low-Earth-Orbit Constellations

arXiv:2608.14789v1 Announce Type: new Abstract: Large low-Earth-orbit (LEO) Earth-observation (EO) constellations offer frequent access to geographically dispersed ground targets, but emergency reques

researcharxiv-cs-ai