Search: “benchmark”

D^2ACCI: A Dual-Loop Diagnostic Protocol for Evidence-Preserving Agent Memory

arXiv:2608.17756v1 Announce Type: new Abstract: Memory is a key capability of LLM agents. Persistent memory extends this across sessions---enabling recall, revision, and personalization. Yet its multi

agentsarxiv-cs-ai

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Agents

DeAR: Decentralized Agentic Reasoning via Capability Grounding and Collaborative Thought Navigation

DGX agent

arXiv:2608.17282v1 Announce Type: new Abstract: Existing agentic reasoning systems typically rely on centralized protocols. This design introduces routing bottlenecks and static role allocations that

agentsarxiv-cs-ai

19 Aug 2026

Deep Academic Survey: Stateful Agentic Closed-Loop Paradigm for Academic Survey Automation

arXiv:2608.18034v1 Announce Type: new Abstract: Academic surveys play a central role in organizing rapidly expanding scholarly literature, yet their construction requires extensive paper analysis, coh

Dijkstra as an Oracle for Online Stochastic Shortest Path Navigation with Provable Guarantees

arXiv:2608.17703v1 Announce Type: cross Abstract: Mobile robots that operate in side by side with humans and critical facilities must reach their goals at low cost, despite often unknown true traversa

researcharxiv-cs-ai

DiSCO: Defending text-to-image generation through distribution-guided contrastive prompt optimization

arXiv:2608.17067v1 Announce Type: new Abstract: As text-to-image generative models advance, they raise critical safety concerns, particularly the generation of Not-Safe-For-Work (NSFW) content such as

DistillPath: An Efficient 22M Distilled Pathology Encoder Approaching Large Foundation Model Performance

arXiv:2608.17872v1 Announce Type: new Abstract: Many high-performing pathology tile encoders are now foundation models with hundreds of millions to over a billion parameters. Encoding and storing the

Do LLMs Know a Good Hypothesis When They See One? Logit-Based Energy Scoring Outperforms Prompted LLM-as-Judge for Scientific Hypothesis Ranking

arXiv:2608.17270v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for scientific hypothesis generation. However, evaluating generated hypotheses remains a challenge fo

Dripper: Token-Efficient Main HTML Extraction with a Lightweight LM

model-releasesarxiv-cs-cl

arXiv:2511.23119v3 Announce Type: replace Abstract: High-quality main content extraction from web pages is a critical prerequisite for constructing large-scale training corpora. While traditional heur

Dynamic Entanglement-Weighted Pruning for Quantum Federated Unlearning in Supply-Chain Risk Prediction

arXiv:2608.17069v1 Announce Type: cross Abstract: Federated deployments of variational quantum classifiers are attractive for cross-organisation risk prediction in supply chains, because raw data neve

Efficient RLVR Scheduling via Graph-Structured Online Difficulty Estimation

arXiv:2608.17941v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models but relies on costly rollout explor

researcharxiv-cs-ai

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification

arXiv:2507.15240v2 Announce Type: replace Abstract: For classification with imbalanced class frequencies, i.e., imbalanced classification (IC), standard accuracy is known to be misleading as a perform

FetchMan: Learning Visual Humanoid Loco-Manipulation Policies from Simulated Experiences

model-releasesarxiv-cs-ro

arXiv:2608.17027v1 Announce Type: new Abstract: Visual loco-manipulation policies that can generalize to novel scenes and objects have long been a goal of robotics research. However, today's data-hung

Fool's Gold: Defensive Deception Against Safety-Removal Attacks on Open-Weight Models

arXiv:2608.17202v1 Announce Type: new Abstract: Safety alignment in open-weight language models is trivially removable: abliteration projects a refusal-mediating direction out of the weights in minute

From Abductive Explanations to Global Logical Rules for Node Classification in SGCs

arXiv:2608.17103v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) have achieved remarkable performance in node classification tasks, motivating growing interest in methods capable of expl

Local Ai

GeoWeaver: Accurate Long-Sequence 3D Reconstruction via Hierarchical Geometric Assembly

arXiv:2608.17389v1 Announce Type: new Abstract: Long-sequence 3D reconstruction from RGB videos requires both accurate local geometry and globally consistent camera motion. Feed-forward models provide

local-aiarxiv-cs-cv

GUPO: Gradient Uncertainty-aware Policy Optimization for Post-Training Large Language Models

arXiv:2608.17411v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has become a widely used approach for post-training Large Language Models (LLMs) for reasoning. In GRPO, the g

safetyarxiv-cs-lg

GxP-Agent: Process-DAG Topology for Reliable Clinical Trial Programming with LLM Agents

arXiv:2608.16890v1 Announce Type: new Abstract: Clinical trial programming -- transforming study protocols into analysis-ready datasets under CDISC standards -- is a bottleneck in regulatory submissio

HeteRo-Select: Informativeness as the Participation Driver in Heterogeneous Federated Learning

arXiv:2508.06692v3 Announce Type: replace Abstract: Federated learning systems typically allocate gradient compression by link speed. This is sensible when bandwidth and data informativeness align. Ho

HODAgent: Towards On-Demand, Responsive Humanoids for Physical World Human Interaction

arXiv:2608.17584v1 Announce Type: new Abstract: We propose HODAgent, a System-2 embodied agent for humanoid robots in service settings, addressing situated intent, responsive execution, task revision,

agentsarxiv-cs-ro

Hydra-0: Action Flow for Generalist World Modeling and Control

model-releasesarxiv-cs-ro

arXiv:2608.18077v1 Announce Type: new Abstract: We introduce Hydra-0, a generalist world model conditioned on action flow, which represents robot actions as pixel motion. This shared visual interface

If, Then, Otherwise: Diagnosing Conditional Branching in Vision-Language Navigation

arXiv:2608.17318v1 Announce Type: new Abstract: Vision-language navigation agents are often evaluated on their ability to follow route-like instructions toward a fixed goal. Yet, real navigation instr

Initialization-Free Bundle Adjustment Revisited: A Controlled Experimental Study

arXiv:2608.18028v1 Announce Type: new Abstract: Initialization-free bundle adjustment (InitFree BA) aims to recover camera poses and scene structure directly from image observations, avoiding the geom

Institution-Specific LLM Prompting Recovers PHI That De-identification Systems and Their Gold Standards Both Miss

arXiv:2608.17051v1 Announce Type: cross Abstract: Secondary use of electronic health records requires de-identification, yet existing systems miss institutionally situated protected health information

safetyarxiv-cs-ai

Judge, Retrieve, or Abstain: Uncertainty-Guarded LLM Judging with Provable Risk Guarantees

arXiv:2608.17994v1 Announce Type: new Abstract: Using LLMs as judges has become standard practice for evaluating model outputs at scale. This is particularly common for subjective, open-ended tasks su

safetyarxiv-cs-cl

KAN We Flow? Advancing Robotic Manipulation with 3D Flow Matching via KAN & RWKV

arXiv:2602.01115v3 Announce Type: replace-cross Abstract: Diffusion-based visuomotor policies excel at modeling action distributions but are inference-inefficient, since recursively denoising from noi

safetyarxiv-cs-cv

KernelArc: A Multi-Agent Framework for GPU Kernel Optimization

arXiv:2608.17071v1 Announce Type: new Abstract: We present KernelArc, a multi-agent framework for autonomous GPU kernel optimization across heterogeneous workloads. Strategy-specialized agents run in

Leveraging existing sparse point annotations for benthic imagery dense segmentation

arXiv:2608.17561v1 Announce Type: new Abstract: The health of marine ecosystems is a critical indicator of global environmental change, yet the physical constraints of underwater observation and the i

Tutorials

Live Interactive Training for Video Segmentation

arXiv:2603.26929v2 Announce Type: replace Abstract: Interactive video segmentation often requires many user interventions for robust performance in challenging scenarios (e.g., occlusions, object sepa

tutorialsarxiv-cs-cv

MaLViL: Multi-axis Low-rank Vision-LSTM for Medical Image Segmentation

arXiv:2608.17635v1 Announce Type: new Abstract: Vision-LSTM (ViL) enables efficient global modeling, but its cost still scales with the number of spatial tokens, so existing segmenters confine ViL to

researcharxiv-cs-cv

Mask What Matters: Saliency-Guided Video Self-Supervised Learning for Autonomous Driving

arXiv:2608.17178v1 Announce Type: new Abstract: Video self-supervised learning through masked spatiotemporal prediction has emerged as a promising paradigm for learning feature representations from un

safetyarxiv-cs-cv

Tutorials

MCTS-KBQA: Monte Carlo Tree Search with Information Gain Rewards for Knowledge Base Question Answering

arXiv:2502.13428v2 Announce Type: replace-cross Abstract: This work investigates how to improve large language model (LLM)-based reasoning for knowledge base question answering (KBQA) via Monte Carlo

tutorialsarxiv-cs-ai

MoE-ViE: Mixture of Experts Vision Encoder for Efficient Image and Video Understanding

arXiv:2608.17402v1 Announce Type: new Abstract: Vision encoders are a critical component of vision-language models, and scaling their capacity effectively improves performance. However, dense scaling

researcharxiv-cs-cv

MoNe: Modular Neural Memory for Efficient Long Context Inference

arXiv:2608.17616v1 Announce Type: new Abstract: We present MoNe, a lightweight modular neural memory that attaches to any frozen pretrained Transformer to enable long-context inference without retrain

MoRA: Mobility as the Backbone for Geospatial Representation Learning at Scale

arXiv:2506.01297v5 Announce Type: replace Abstract: Representation learning of geospatial locations remains a core challenge in achieving general geospatial intelligence, with increasingly diverging p

MS-MFAD : Multimodal large language models for Face Anti-spoofing Detection

arXiv:2608.17328v1 Announce Type: new Abstract: Facial biometric recognition systems currently face compound threats intertwining generative AI and high-fidelity physical spoofing. Existing defenses s

MSEditor: Toward Consistent Multi-Shot Video Editing

arXiv:2608.17559v1 Announce Type: new Abstract: In this paper, we tackle the problem of performing consistent, unified modifications to a multi-shot video sequence. This task is particularly challengi

Applications

Multi-Observer Vehicle Localization Case Study with Roadside Radar and Connected Vehicle Sensing

arXiv:2608.16966v1 Announce Type: new Abstract: In modern intelligent transportation systems, it is essential to accurately estimate vehicle positions, especially in mixed traffic conditions where bot

applicationsarxiv-cs-cv

Multi-turn Conversational AI from Text to Multimodal Interaction: Data, Models, Evaluation, and Open Challenges

arXiv:2608.17605v1 Announce Type: cross Abstract: Conversational AI is moving beyond isolated text prompts toward sustained, multimodal interaction. In real conversations, users clarify goals, revise

safetyarxiv-cs-ai

Neural Operator-Based Nonlinear Nudging for Chaotic Dynamical Systems

arXiv:2508.05778v2 Announce Type: replace Abstract: Nudging is an empirical data assimilation technique that incorporates an observation-driven control term into the model dynamics. The trajectory of

Nonadaptive Learning in Robust Nonlinear Output Regulation

arXiv:2608.17262v1 Announce Type: cross Abstract: This paper considers robust nonadaptive regulation for general nonlinear systems in an output-feedback setting with arbitrarily high relative degree.

OraclePhys: A Systematic Framework for LLM Fine-Tuning on Structural Mechanics

arXiv:2608.17162v1 Announce Type: new Abstract: What a language model internalizes from fine-tuning is usually diagnosed after the fact. We make it an experimental variable. OraclePhys is a systematic

PlanPO: Group Planning-Aware Policy Optimization for Multi-Turn Agentic LLMs

arXiv:2608.17289v1 Announce Type: new Abstract: Group-relative policy optimization has emerged as a key paradigm for training agentic large language models (LLMs) on multi-turn interactive tasks. Howe

safetyarxiv-cs-ai

Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving

arXiv:2608.18035v1 Announce Type: new Abstract: Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driv

PRISM: Precision and contact-rich Real-world Industrial Skill dataset with Multimodal sensing

model-releasesarxiv-cs-ro

arXiv:2608.17962v1 Announce Type: new Abstract: Recent progress in robotic learning has been fueled by large-scale datasets collected in everyday environments. However, most existing datasets emphasiz

PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training

arXiv:2602.13840v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed in personalized tasks involving sensitive, context-dependent information, where privacy

agentsarxiv-cs-cl

Proactive Road Safety Intervention in Australia: Predicting Risky Driving Hotspots from Connected Vehicle Data

arXiv:2608.16913v1 Announce Type: new Abstract: Road safety monitoring has historically been reactive, relying on crash-record analysis after fatalities and injuries have already occurred. Proactive i

safetyarxiv-cs-lg

PROBE: Manipulation-Grounded Visual Question Answering with VLM Agents

arXiv:2608.17129v1 Announce Type: new Abstract: Vision-language Models (VLMs) excel at 2D grounding, spatial reasoning and agentic tool-based planning in static scenes. However, consider asking a home

agentsarxiv-cs-cv

Local Ai

PXDepth: Pixel-Space Modeling for Structure Preserving Monocular Depth Estimation

arXiv:2608.16984v1 Announce Type: cross Abstract: Recent monocular depth estimators achieve strong zero-shot generalization, yet often struggle to preserve fine-grained structures and object boundarie

local-aiarxiv-cs-ai