Search: “benchmark”

Agentic-Kube: A Graph-Enhanced Multi-Agent Reinforcement Learning Framework for Multi-Objective Kubernetes Scheduling

arXiv:2603.12031v3 Announce Type: replace-cross Abstract: Cloud-native container orchestration requires resource schedulers capable of balancing infrastructure expenditure, fault resilience, and node

safetyarxiv-cs-lg

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Agents

An Information-Flow Perspective on Explainability Requirements: Specification and Verification

DGX agent

arXiv:2509.01479v3 Announce Type: replace-cross Abstract: Explainable systems expose information about why certain observed effects are happening to the agents interacting with them. We argue that thi

agentsarxiv-cs-ai

25 Aug 2026

AquaFlow: A Monocular Gaussian Splatting SLAM for Underwater Streaming Reconstruction

arXiv:2608.22906v1 Announce Type: new Abstract: Recent monocular 3D Gaussian Splatting (3DGS) streaming reconstruction methods have achieved impressive performance by balancing reconstruction quality

researcharxiv-cs-cv

Arbitrage-Aware Multi-Step Forecasting of Implied Volatility Surfaces: Modelling Surface Trajectories Using Latent Diffusion

arXiv:2608.22478v1 Announce Type: cross Abstract: Implied volatility surfaces summarise the option market and are central to many financial applications. Forecasting their future evolution requires mo

ARCHER: Amortized cross-specimen pose estimation for cryo-electron microscopy

arXiv:2608.22029v1 Announce Type: new Abstract: Single-particle cryo-electron microscopy (cryo-EM) pose estimation is traditionally solved anew for each dataset, where iterative refinement is done fro

researcharxiv-cs-lg

ATP-Bench: Towards Agentic Tool Planning for MLLM Interleaved Generation

arXiv:2603.29902v2 Announce Type: replace Abstract: Interleaved text-and-image generation represents a significant frontier for Multimodal Large Language Models (MLLMs), offering a more intuitive way

AUDITA: certified auditing and causal attribution of adverse outcomes in autonomous multi-agent systems

arXiv:2608.22160v1 Announce Type: new Abstract: Physical automation is scaling toward fleets of embodied machines commanded by an AI brain. Early deployments already run factories and warehouses at pr

BC-IHV: Conditioning the Color Space for Stable Rectified-Flow Low-Light Enhancement

arXiv:2608.21847v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) must correct ambiguous exposure without overwriting structure already supported by the input. Generative transport ca

researcharxiv-cs-cv

Beyond Dense Adam States: Adaptive Log-Space Quantization for Memory-Efficient Optimizers

arXiv:2608.22322v1 Announce Type: new Abstract: Low-precision optimizer-state methods are commonly designed for dense Adam-style moments, but memory-efficient optimizers maintain factored, confidence-

Beyond Fresh Starts: Stateful Inference for Streaming ASR in Conversational Voice Agents

arXiv:2608.22101v1 Announce Type: new Abstract: Modern voice-agent systems rely on streaming speech recognition models that operate under stringent latency constraints. This study shows that, due to t

agentsarxiv-cs-lg

Beyond Success and Failure: Length-Aware Contrastive Learning for GUI Agents

arXiv:2608.21830v1 Announce Type: new Abstract: Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) have shown strong potential for automating tasks across divers

safetyarxiv-cs-ai

Beyond the Stability-Exploration Dilemma: Environmental Regularization for LLM Policy Optimization

arXiv:2608.23311v1 Announce Type: new Abstract: Policy optimization (PO) for Large Language Models faces a stability--exploration trade-off, currently mediated by an action-side Policy-KL regularizer.

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Beyond What Meets the Eye: Unveiling Situational Illusions for Multimodal Large Language Models

arXiv:2608.22232v1 Announce Type: new Abstract: Real-world situation appearances can deviate from their underlying physical states, challenging the reliability of multimodal large language models (MLL

Big step forward for Engine! Some things I'm excited about in this release that we've shipped for our most avid users: - Engine now points m…

Big step forward for Engine! Some things I'm excited about in this release that we've shipped for our most avid users: - Engine now points more obviously to the issue in a trace. Engine identifies and

agentsharrison-chase--x

BioMed-Agent-RL: A Meta Learning, All You Need for Biomedical Applications

arXiv:2608.21864v1 Announce Type: cross Abstract: The current progress of Clinical Vision Large Language Models (C-VLLMs) has substantially improved digital diagnostics, still these frameworks often e

Boosting Knowledge-based Visual Question Answering with Structured Context Reasoning

arXiv:2608.21431v1 Announce Type: new Abstract: Knowledge-based Visual Question Answering aims to answer questions about an image by integrating external knowledge with visual and textual information.

researcharxiv-cs-cv

Applications

Bounded Precision-Geometry Scaling for Robust Multi-Task Learning under Loss Scale Mismatch

arXiv:2608.21653v1 Announce Type: cross Abstract: Multi-task learning often combines losses that span several orders of magnitude, causing homoscedastic uncertainty weighting to degrade severely. We p

applicationsarxiv-cs-cv

Bulbul: A Dataset for Dialectal Arabic Speech Recognition

arXiv:2608.21950v1 Announce Type: cross Abstract: Arabic automatic speech recognition (ASR) faces unique challenges due to diglossia, extensive regional dialect variation, and limited speech resources

Buried in Textual Debt: Context Pruning with Visual Evidence Preservation for MLLM Agents

arXiv:2608.22963v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed as multi-step agents, where explicit reasoning supports task decomposition and tool c

safetyarxiv-cs-ai

CALIBURN: Self-Calibrated LLM Unlearning Alignment

arXiv:2602.02824v2 Announce Type: replace Abstract: LLM unlearning aims to remove the influence of undesirable knowledge from pretrained language models, which offers a practical mechanism for address

safetyarxiv-cs-cl

Can Coding Agents Build Robust Baselines? A Skill-Based Approach for Automating the Medical Imaging Model-Development Pipeline

arXiv:2608.23336v1 Announce Type: new Abstract: Developing competitive deep learning baselines for medical imaging remains a highly iterative process requiring literature review, implementation, exper

agentsarxiv-cs-cv

Can LLMs Truly Forget? Revealing Unlearning Gaps Through Adversarial Evaluation

model-releasesarxiv-cs-cl

arXiv:2608.21606v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of targeted training data from a model while preserving its remaining capabilities, but evaluating wheth

CDEG: Learning Decision-Critical Evidence for Long-Horizon Diagnostic Agents

arXiv:2608.22899v1 Announce Type: new Abstract: Unlike static medical question answering, long-horizon diagnosis captures the sequential nature of clinical practice: evidence is progressively acquired

agentsarxiv-cs-ai

ClinicalGPT-R1: Pushing reasoning capability of generalist disease diagnosis with large language model

arXiv:2504.09421v3 Announce Type: replace-cross Abstract: Recent advances in reasoning with large language models (LLMs)has shown remarkable reasoning capabilities in domains such as mathematics and c

Compositional Chain-of-Relations for Faithful Knowledge Graph Question Answering with Large Language Models

arXiv:2608.22762v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) is a key task for evaluating KG-augmented Large Language Models (LLMs), and complex KGQA that requires multi-h

agentsarxiv-cs-ai

Contact-Rich Robotic Manipulation in Construction via Zero-Shot Learning: A Diffusion Policy-Guided Adaptive Control

model-releasesarxiv-cs-ro

arXiv:2608.22100v1 Announce Type: new Abstract: Construction robotics and automation offer promising means of improving productivity, alleviating workforce shortages, and reducing workers' exposure to

Local Ai

Context-Aware Cluster Decoding: Semantic Anchor-Driven Coherence in dMLLMs

arXiv:2608.22367v1 Announce Type: new Abstract: Diffusion multimodal large language models (dMLLMs) frequently produce long-form outputs marred by semantic drift and repetition, with quality generally

local-aiarxiv-cs-cl

CounterAlign: Counterfactual Supervision for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2608.21740v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are typically trained with behavior cloning (BC) on expert demonstrations. However, BC provides only positive superv

Cross-Domain, Multi-Task Data-to-Text Generation without In-Domain Training Data

arXiv:2608.23391v1 Announce Type: cross Abstract: Structured data exists in many forms (tables, knowledge graphs, charts, and time series), and converting it into text may involve different generation

researcharxiv-cs-ai

Cross-lingual Biography Enrichment via Claim Extraction and Alignment

arXiv:2608.23390v1 Announce Type: cross Abstract: English Wikipedia is often treated as the default encyclopedic source, yet non-English Wikipedia editions can contain richer locally grounded informat

Hardware

CST: Collaborative Selective Transmission for Communication-Efficient Multimodal Edge Inference

arXiv:2608.22115v1 Announce Type: new Abstract: Collaborative multimodal inference improves edge perception by combining observations from distributed sensing devices, but transmitting high-dimensiona

hardwarearxiv-cs-lg

CSymPlan: Certified Symbolic Planning and Control for High-DOF Manipulators

arXiv:2608.22983v1 Announce Type: new Abstract: Robot manipulators are commonly engineered around a decoupled motion-generation stack: a planner computes a collision-free path and a lower-level contro

safetyarxiv-cs-ro

DelistBench: Evaluating Search-Enabled LLMs for Auditable Corporate-Event Database Completion

model-releasesarxiv-cs-cl

arXiv:2608.22770v1 Announce Type: new Abstract: Financial institutions need an independent way to detect missing, stale, and misclassified corporate-event records in vendor databases. We introduce Sea

DeltaGNN: Graph Neural Network with Information Flow Control

arXiv:2501.06002v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) are popular deep learning models designed to process graph-structured data through recursive neighborhood aggregations

Development and Feasibility Evaluation of an Edge AI as Medical Device System for Breast Cancer Multidisciplinary Team Meetings

arXiv:2608.22108v1 Announce Type: new Abstract: Breast Cancer Multidisciplinary Team (MDT) meetings manage increasingly complex cases under considerable time pressure, and documentation requirements c

DF-MoE: Generalizable Deepfake Detection via Multimodal Sparse Mixture-of-Experts

arXiv:2608.23363v1 Announce Type: cross Abstract: Audio-visual deepfake detection is an actively studied topic, where one of the main challenges is to develop detectors able to generalize across deepf

researcharxiv-cs-ai

DiagFlowBench: Evaluating How Language Models Handle Off-Procedure Inputs in Grounded Diagnostic Dialogue

arXiv:2606.17904v2 Announce Type: replace Abstract: Language models increasingly serve as advisory systems in maintenance operations. To prevent hallucination, recent systems ground these models in pr

researcharxiv-cs-ai

Disagree to Explore, Agree to Commit: Routing-Guided Test-Time Scaling for Software Agents

arXiv:2608.22191v1 Announce Type: new Abstract: Software-engineering agents solve repository-level tasks through long, stochastic tool-use trajectories, and repeated attempts often find fixes missed b

Do Large Language Models Perform Well on Comprehending Poetic Logic in Modern Chinese Poetry?

model-releasesarxiv-cs-cl

arXiv:2608.21827v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved significant progress across a wide range of natural language processing (NLP) tasks, yet their ability to und

Do Spoken Language Models Hear Speech as They Read Text? Bridging Structural Gaps Between Speech and Text

arXiv:2608.22908v1 Announce Type: cross Abstract: Spoken Language Models (SLMs) generate textual responses directly from speech, offering an alternative to cascaded systems. Despite recent advances, e

safetyarxiv-cs-ai

Does a Modern-Handwriting Warm-Up Help Historical Arabic OCR? A Reproducible, Compute-Matched Evaluation on Muharaf and KHATT

model-releasesarxiv-cs-cv

arXiv:2608.22316v1 Announce Type: cross Abstract: Whether an intermediate stage of modern Arabic handwriting helps or hurts historical Arabic HTR is usually decided from one implementation and one com

Don' t Box Me In: Dynamic Cultural Adaptation and Cognitive Tracking for Social Understanding

arXiv:2608.22411v1 Announce Type: new Abstract: Social interaction increasingly takes place in multicultural settings, where individuals may draw on multiple cultural influences and adapt their commun

safetyarxiv-cs-cl

DuoGNN: Topology-aware Graph Neural Network with Homophily and Heterophily Interaction-Decoupling

arXiv:2409.19616v3 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have proven effective in various medical imaging applications, such as automated disease diagnosis. However, due to the

DynaContext: Self-Improving Dynamic Contextualization of Optimized Prompts for Heterogeneous Parameter Extraction

arXiv:2608.22014v1 Announce Type: new Abstract: Automated prompt and skill optimization typically produces a single static instruction that is reused across inference instances until the next optimiza

DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning

arXiv:2603.16459v2 Announce Type: replace Abstract: Diffusion large language models (D-LLMs) have emerged as a promising alternative to auto-regressive models due to their iterative refinement capabil

researcharxiv-cs-cl

Tutorials

EchoWM: Open and Enterable Omnimodal World Models

arXiv:2608.23189v1 Announce Type: new Abstract: We present EchoWM, an omnimodal world model for enterable generative media that responds to continuous navigation while jointly generating 720p video, e

tutorialsarxiv-cs-cv

ENCORE: Entropy-Guided Cropping and Attention Regularization for Robust Vision--Language Understanding

model-releasesarxiv-cs-cv

arXiv:2608.22996v1 Announce Type: new Abstract: Vision-Language Models (VLMs) perform well on diverse vision-language tasks, but transformer-based visual encoders split images into fixed-resolution su

Tutorials

Every extraction API demos well on a clean invoice. But what about the scanned form, the nested table, the 40-page financial report with mer…

Every extraction API demos well on a clean invoice. But what about the scanned form, the nested table, the 40-page financial report with merged headers? We tested 14 frontier systems to find out. Extr

tutorialsllamaindex--x