All entries

PIT-SUN: A Deployable Empirical Marginal Transform Framework with Expectation-Consistent Recovery for Regression in Recommender Systems

arXiv:2607.08202v1 Announce Type: new Abstract: Estimating original-space conditional expectations is central to value-driven recommender systems, including dwell time, GMV, and LTV forecasting. Stand

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Agents

Playing ZendoWorld: Challenging AI Agents on Active Visual Concept Induction

DGX agent

arXiv:2607.08233v1 Announce Type: new Abstract: A central challenge in building intelligent systems is enabling agents to jointly perceive complex inputs, form hypotheses about hidden patterns, and de

agentsarxiv-cs-ai

10 Jul 2026

PLURAL: A Global Dataset for Value Alignment

arXiv:2607.08034v1 Announce Type: cross Abstract: Large language models (LLMs) are used worldwide, yet disproportionately reflect Western values, limiting their ability to represent diverse value syst

safetyarxiv-cs-ai

PolyUQuest: Verifiable Structure-Aware Web RAG over Heterogeneous Graphs

arXiv:2607.08269v1 Announce Type: new Abstract: Existing retrieval-augmented generation (RAG) systems treat web pages as flat text, losing the structural and semantic signals encoded in HTML. We prese

Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction

arXiv:2607.08725v1 Announce Type: cross Abstract: Recent progress in 3D human pose estimation has made markerless recovery of skeletal motion increasingly accurate and scalable. However, most pose est

Post-Training in End-to-End Autonomous Driving

arXiv:2607.08072v1 Announce Type: new Abstract: End-to-end models that map multimodal inputs directly to future trajectories/maneuvers have emerged as an increasingly prominent research paradigm in au

safetyarxiv-cs-cv

Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs

arXiv:2310.07895v2 Announce Type: replace Abstract: This paper presents a method to efficiently classify the gastroenterologic section of images derived from Video Capsule Endoscopy (VCE) studies by e

Predicting Male Fertility Using Machine Learning: A Semen Parameters Based Analysis with the VISEM Dataset

arXiv:2607.08429v1 Announce Type: cross Abstract: Male infertility is a significant yet often underdiagnosed aspect of reproductive health, with semen analysis serving as the cornerstone of clinical e

Applications

Predicting Pseudo-nitzschia harmful algal blooms along the Portuguese Coast using satellite-derived predictors

arXiv:2607.07834v1 Announce Type: new Abstract: Pseudo-nitzschia diatoms pose recurrent risks to coastal ecosystems and shellfish harvesting along the Portuguese Atlantic coast. Here we develop and ev

applicationsarxiv-cs-lg

Predicting Viticulture Potential through an Ensemble of U-Net and a Geospatial Foundation Model

arXiv:2607.08449v1 Announce Type: new Abstract: Determining agricultural potential is fundamental to sustainable land management and agricultural planning. Remote sensing data is increasingly valuable

Prediction-Powered Active Testing

arXiv:2607.08347v1 Announce Type: cross Abstract: Active testing provides a label--efficient approach to risk estimation by adaptively selecting which test points should be labelled. However, existing

PRGCN: A Graph Memory Network for Cross-Sequence Pattern Reuse in 3D Human Pose Estimation

arXiv:2510.19475v2 Announce Type: replace Abstract: Monocular 3D human pose estimation remains a fundamentally ill-posed inverse problem due to the inherent depth ambiguity in 2D-to-3D lifting. While

Principled Analysis of Deep Reinforcement Learning Evaluation and Design Paradigms

arXiv:2607.07769v1 Announce Type: cross Abstract: Starting from the utilization of deep neural networks to approximate the state-action value function that led to winning one of the most challenging g

Prismata: Confining Cross-Site Prompt Injection in Web Agents

arXiv:2607.08147v1 Announce Type: cross Abstract: Autonomous web agents promise to automate everyday browsing tasks, but inherit one of the web's oldest attack surfaces. Cross-Site Scripting proved th

safetyarxiv-cs-ai

Progression as Latent Drift: Generative Forecasting of Slow-Evolving Pathologies

arXiv:2607.08270v1 Announce Type: new Abstract: Forecasting the future anatomy of slow-evolving neurodegenerative diseases could enable earlier, more targeted intervention and improve clinical trial d

local-aiarxiv-cs-cv

Agents

ProjAgent: Procedural Similarity Retrieval for Repository-Level Code Generation

arXiv:2607.08691v1 Announce Type: cross Abstract: Repository-level code generation requires implementing target functions while accounting for complex cross-file dependencies and project-specific conv

agentsarxiv-cs-ai

Prompt Compression via Activation Aggregation

arXiv:2607.08399v1 Announce Type: new Abstract: Large language models process prompts by propagating activations through dozens of layers before generating a response. We ask whether the task-relevant

researcharxiv-cs-cl

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification

arXiv:2607.08162v1 Announce Type: cross Abstract: Whole slide images (WSIs) provide rich diagnostic information for computational pathology, but their gigapixel scale, stain variation, scanner differe

Provable Subspace Identification of Nonlinear Multi-view CCA

arXiv:2602.23785v2 Announce Type: replace Abstract: We investigate the identifiability of nonlinear canonical correlation analysis (CCA) in a multi-view setup, in which each view is generated by apply

Agents

Provably Optimal Learning Algorithms for Assistance Games

arXiv:2607.08012v1 Announce Type: cross Abstract: This paper studies an online variant of the assistance games framework, where an informed agent and an uninformed agent repeatedly interact over T tim

agentsarxiv-cs-ai

PS4: Proxy-Supervised Joint Training for Real Target Speaker Extraction

arXiv:2607.08111v1 Announce Type: cross Abstract: Training target speaker extraction (TSE) models for real conversational mixtures remains challenging because large-scale training corpora and clean ta

Psychological Competence as a Missing Dimension in AI Evaluation

arXiv:2607.08285v1 Announce Type: new Abstract: Current AI evaluation frameworks focus primarily on technical performance, including accuracy, robustness, reasoning ability, and policy compliance. The

RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization

arXiv:2607.08045v1 Announce Type: cross Abstract: Angular radio maps describe the received-power distribution over the angle of arrival and underpin beam selection and receiver localization in sixth-g

local-aiarxiv-cs-lg

RadLoc: Radar-based 3-DoF Global Localization via Fast, Robust, and Lightweight Spatial Descriptor Across Diverse Environmental Scenarios

arXiv:2607.08115v1 Announce Type: new Abstract: While global localization using spinning radar has gained attention for its robustness to adverse weather and challenging environments, many studies hav

researcharxiv-cs-ro

Applications

Reaction-network reasoning with frontier models for experimentally confirmed catalyst-selectivity hypotheses

arXiv:2607.08003v1 Announce Type: cross Abstract: Catalysts are essential for sustainable chemical manufacturing, yet discovering novel architectures remains a bottleneck dominated by trial-and-error

applicationsarxiv-cs-ai

Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors

model-releasesarxiv-cs-cv

arXiv:2202.13142v3 Announce Type: replace Abstract: A key challenge of real-world image super-resolution (SR) is to recover the missing details in low-resolution (LR) images with complex unknown degra

ReCoLoRA: Spectrum-Aware Recursive Consolidation for Continual LLM Fine-Tuning

arXiv:2607.07719v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning adapts a large language model to one task cheaply, but across a task sequence LoRA-style methods keep stacking low-ran

Reinforcing the Generation Order of Multimodal Masked Diffusion Models

arXiv:2607.08056v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that a

Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents

arXiv:2607.08716v1 Announce Type: new Abstract: In long-horizon tasks, decision-relevant state is often scattered across an expanding trajectory, while the action agent must surface it and act. As tra

Resample or Reroute? Budget-Aware Test-Time Model Selection for Large Language Models

model-releasesarxiv-cs-lg

arXiv:2607.08665v1 Announce Type: new Abstract: Routing among large language models (LLMs) trades response quality against serving cost, motivated by the reported gap between deployed routers and a pe

Resolving Predictive Multiplicity for the Rashomon Set

arXiv:2601.09071v2 Announce Type: replace Abstract: The existence of multiple, equally accurate models for a given predictive task leads to predictive multiplicity, where a Rashomon set of models achi

local-aiarxiv-cs-lg

RetailBench: Evaluating Long-Horizon Autonomous Decision-Making and Strategy Stability of LLM Agents in Realistic Retail Environments

arXiv:2603.16453v3 Announce Type: replace Abstract: Large language model (LLM) agents have made rapid progress on short-horizon, well-scoped tasks, yet their ability to sustain coherent decisions in d

Rethinking LLM-as-a-Judge: Representation-as-a-Judge with Small Language Models via Semantic Capacity Asymmetry

arXiv:2601.22588v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used as reference-free evaluators via prompting, but this 'LLM-as-a-Judge' paradigm is costly, opaque,

Rethinking Small VLM Quantization: From Component-Wise Analysis to Hardware-Aware Edge Deployment

arXiv:2607.08029v1 Announce Type: new Abstract: The emergence of vision language models with fewer than 3 billion parameters has accelerated the implementation of on-device multimodal intelligence. Ho

local-aiarxiv-cs-lg

Retrieval of Scientific and Technological Resources for Experts and Scholars

arXiv:2204.06142v2 Announce Type: replace-cross Abstract: Institutions of higher learning, research institutes and other scientific research units have abundant scientific and technological resources

Revisiting One-Zero and Two-Zero Neutrino Mass Textures in Light of Recent Oscillation and Cosmological Data

arXiv:2607.08384v1 Announce Type: cross Abstract: We revisit one-zero and two-zero textures of the neutrino mass matrix under current experimental and cosmological constraints. We identify the phenome

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting

arXiv:2607.08234v1 Announce Type: cross Abstract: Real-world time series exhibit complex dynamics characterized by multiple simultaneous temporal patterns: short-term fluctuations, periodic seasonal c

local-aiarxiv-cs-ai

Applications

Robust Bayesian Decision Making under Adversarial Uncertainty

arXiv:2607.08590v1 Announce Type: new Abstract: Scientific experiments are often designed to maximize information gain, yet in many applications the primary objective is to support reliable downstream

applicationsarxiv-cs-lg

Robust Weighted Triangulation of Causal Effects Under Model Uncertainty

arXiv:2603.01119v2 Announce Type: replace-cross Abstract: A fundamental challenge in causal inference with observational data is correct specification of a causal model. When there is model uncertaint

Robustness Quantification for Discriminative Models: a New Robustness Metric and its Application to Dynamic Classifier Selection

arXiv:2603.23318v2 Announce Type: replace Abstract: Among the different possible strategies for evaluating the reliability of individual predictions of classifiers, robustness quantification stands ou

Safe Flow Q-Learning: Offline Safe Reinforcement Learning with Reachability-Based Flow Policies

arXiv:2603.15136v2 Announce Type: replace-cross Abstract: Offline safe reinforcement learning (RL) seeks reward-maximizing policies from static datasets under strict safety constraints. Existing metho

safetyarxiv-cs-ai

SAGA: Stable Acceleration Guidance for Autoregressive Video Generation

arXiv:2607.08020v1 Announce Type: new Abstract: Autoregressive video diffusion enables efficient streaming and long-horizon video generation, but repeatedly reusing generated latents as causal context

SAM-MT: Real-Time Interactive Multi-Target Video Segmentation

arXiv:2607.08688v1 Announce Type: new Abstract: Modern Video Object Segmentation (VOS) involves tracking and segmenting user-specified targets. While recent approaches have achieved remarkable perform

SASGeo: Stability-Aware Semantic Map Localization for GNSS-Denied UAVs -- A Framework and Synthetic Proof of Concept

arXiv:2607.07737v1 Announce Type: cross Abstract: GNSS-denied unmanned aerial vehicles require occasional absolute position fixes to bound the drift of visual-inertial odometry. Cross-view image retri

safetyarxiv-cs-cv

Scalable and Culturally Specific Stereotype Dataset Construction via Human-LLM Collaboration

arXiv:2607.07895v1 Announce Type: new Abstract: Research on stereotypes in large language models (LLMs) has largely focused on English-speaking contexts, due to the lack of datasets in other languages

safetyarxiv-cs-cl

Scalable and Trustworthy Earth Observation Foundation Models

model-releasesarxiv-cs-lg

arXiv:2607.07758v1 Announce Type: new Abstract: Foundation models (FMs) have transformed machine learning from isolated task-specific model development toward general-purpose models pretrained on broa

Score Accuracy Along the Forward Diffusion Does Not Certify Numerical Stability in Diffusion Sampling

arXiv:2607.08757v1 Announce Type: cross Abstract: Score matching controls average error under the forward marginals, but a discretized reverse-time sampler evaluates the learned score along its own tr

Search-based Testing of Vision Language Models for In-Car Scene Understanding

arXiv:2607.02300v2 Announce Type: replace Abstract: In the automotive domain, in-car scene understanding (ISU) enables the detection of safety-critical events, such as driver distraction, and supports

safetyarxiv-cs-cv