Search: “benchmark”

Toward Robust LLM-Based Judges: Taxonomic Bias Evaluation and Debiasing Optimization

model-releasesarxiv-cs-cl

arXiv:2603.08091v2 Announce Type: replace Abstract: Large language model (LLM)-based judges are widely adopted for automated evaluation and reward modeling, yet their judgments are often affected by j

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Towards Anomaly Detection on Relational Data

DGX agent

arXiv:2606.18621v2 Announce Type: replace Abstract: Relational databases are widely used for managing structured data in real-world systems. Detecting anomalies from such relational data is crucial fo

model-releasesarxiv-cs-lg

4 Aug 2026

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning

arXiv:2608.01488v1 Announce Type: new Abstract: Unified multimodal object tracking has achieved remarkable robustness by leveraging complementary sensor data (e.g., RGB, Thermal, Depth), yet the heavy

TRACE-TS: Attribution-Grounded and Traceable Sensor-Language Reasoning for Human Activity Understanding

arXiv:2608.00200v1 Announce Type: cross Abstract: Wearable sensors capture fine-grained motion patterns that support rich behavioral understanding, yet most existing methods reduce these signals to ac

local-aiarxiv-cs-cl

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes

arXiv:2608.02415v1 Announce Type: new Abstract: Intent classification in Large Language Models (LLMs) involves categorizing user prompts into predefined classes. For instance, given a user prompt, the

TRAM: Enhancing Multimodal Reasoning with Trajectory-Derived Auxiliary Memory

arXiv:2608.01922v1 Announce Type: new Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved strong performance on tasks requiring visual understanding and multi-step inference. However, as

Trustworthiness Costs of Domain Adaptation in Small Language Models:A Cross-Architecture Empirical Study

model-releasesarxiv-cs-cl

arXiv:2608.00042v1 Announce Type: new Abstract: Domain adaptation of small language models (SLMs) has emerged as a practical strategy for deploying capable NLP systems in resource-constrained, high-st

TS-Reasoner: Aligning Time Series Foundation Models with LLM Reasoning

arXiv:2510.03519v2 Announce Type: replace Abstract: Time series reasoning is crucial to decision-making in diverse domains, including finance, energy, and scientific discovery. While existing time ser

safetyarxiv-cs-cl

UCBound-Net: Uncertainty-Guided Boundary-Aware Continual Learning for Domain-Incremental Ultrasound Segmentation

arXiv:2608.01518v1 Announce Type: new Abstract: Continual learning in clinical imaging faces a dual challenge: a model must assimilate knowledge from new anatomical domains while retaining representat

Uncertainty-Aware Simulation-Based Inference for Operations Research with Large Language Models

arXiv:2608.00019v1 Announce Type: new Abstract: Deploying large language models (LLMs) for operations research (OR) tasks remains challenging because correctness depends on a coherent modeling process

local-aiarxiv-cs-lg

Uncovering and Mitigating Positional Blind Spots in Vision-Language-Action Models

arXiv:2608.01573v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models achieve promising performance in robotic manipulation, typically measured by success rates aggregated over pr

safetyarxiv-cs-ro

Understanding Synergistic Interactions among Pathology Foundation Models via Adaptive Fusion

arXiv:2608.01370v1 Announce Type: new Abstract: Pathology foundation models (PFMs) provide strong tile-level representations via self-supervised pre-training on large-scale pathology images. Yet, PFMs

Tutorials

Unleashing the Power of Text: Text-Guided Flow Matching for Image Fusion under Complex Degradations

arXiv:2608.00530v1 Announce Type: new Abstract: Infrared-visible image fusion under realistic degradation scenarios is a challenging task, as degradations not only cause a loss of reliable modality-sp

tutorialsarxiv-cs-cv

Applications

VaRS-Doc: Interpretation-Aware Variant Representations via Latent Self-Probing for Visual Document Retrieval

arXiv:2608.01211v1 Announce Type: new Abstract: Visual document retrieval has recently become increasingly important in applications such as enterprise search, scientific literature discovery, and ret

applicationsarxiv-cs-cv

VC-Tooler: Learning Compositional and Adaptive Visual Tool Use

arXiv:2608.02217v1 Announce Type: new Abstract: Agentic multimodal reasoning extends passive image understanding by allowing VLMs to actively acquire and refine visual evidence through visual tool int

agentsarxiv-cs-cv

Verifier-Induced Support Reshaping in On-Policy Optimization

arXiv:2608.00220v1 Announce Type: cross Abstract: We show that on-policy reinforcement learning with verifiable rewards (RLVR) can improve the current objective while making successful behaviors for l

safetyarxiv-cs-cl

VGER: Voxel-Guided Global Event Ranking for Event Cloud Attribution

arXiv:2608.01470v1 Announce Type: new Abstract: Event cameras produce sparse and asynchronous event streams that provide rich spatio-temporal information for efficient perception. Recent advances in e

Video Models as Native 4D Renderers: World-Grounded Conditioning from Animated Mesh

arXiv:2608.00094v1 Announce Type: new Abstract: Pretrained video diffusion models can act as renderers when the desired scene state is already specified by an animated mesh, a camera trajectory, and a

VR3D: View-Robust 3D Representation Learning for Aerial-Ground Person Re-Identification

arXiv:2608.02598v1 Announce Type: new Abstract: Aerial-ground person re-identification is a challenging task due to cross-platform viewpoint variations, which cause severe occlusion and geometric defo

WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA

arXiv:2608.01035v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a prominent paradigm for end-to-end autonomous driving; however, their efficient deployment is sev

When Collaboration Becomes a Trigger: Collective Evidence-Threshold Backdoors in Multi-Agent Systems

arXiv:2608.01085v1 Announce Type: cross Abstract: LLM-based multi-agent systems (MAS) extend LLM capabilities through iterative communication and shared contexts. However, this collaboration introduce

agentsarxiv-cs-lg

Which Modality Decides? Counterfactual Modality Attribution for Multimodal LLMs

arXiv:2608.00076v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) increasingly support high-stakes decision making by combining complementary information from images and text. W

Why Large Language Models Fail at Tabular Prediction

arXiv:2608.02412v1 Announce Type: new Abstract: Large language models (LLMs) have become the default tool for a remarkable range of tasks, yet they have had conspicuously little success at one of the

WorldMirror: Universal 3D World Reconstruction with Any-Prior Prompting

arXiv:2510.10726v2 Announce Type: replace Abstract: We present WorldMirror, a unified feed-forward model for comprehensive 3D geometric prediction tasks. Unlike existing methods constrained to image-o

AMTFV: Agentic Mathematical Tool-Flow Verification for LLM Self-Correction

model-releasesarxiv-cs-ai

arXiv:2607.29549v1 Announce Type: new Abstract: Large language models have demonstrated strong mathematical problem-solving capabilities, yet reliably verifying their candidate answers remains challen

AREA3D: Active Reconstruction Agent with Unified Feed-Forward 3D Perception and Vision-Language Guidance

arXiv:2512.05131v2 Announce Type: replace-cross Abstract: Active 3D reconstruction enables an agent to autonomously select viewpoints to efficiently obtain accurate and complete scene geometry, rather

agentsarxiv-cs-ai

Artifact detection and localization in single-channel mobile EEG for sleep research using deep learning and attention mechanisms

arXiv:2504.08469v3 Announce Type: replace-cross Abstract: Current methods for detecting artifacts in sleep EEG range from threshold-based algorithms to machine learning approaches, yet applications re

local-aiarxiv-cs-lg

Artificial Analysis: DeepSeek's V4-Flash costs 0.14/1M input and 0.28/1M output tokens, or 0.03 per test, far below Kimi K3's 0.86 and GPT-5.6 Sol's $1.86 (Eduardo Baptista/Reuters)

Eduardo Baptista / Reuters: Artificial Analysis: DeepSeek's V4-Flash costs 0.14/1M input and 0.28/1M output tokens, or 0.03 per test, far below Kimi K3's 0.86 and GPT-5.6 Sol's $1.86 — A version of Ch

model-releasestechmeme

Assessing the Generalization of Graph Neural Networks for Fault Location Across Increasing Distributed Energy Resource Penetration Levels

arXiv:2607.29293v1 Announce Type: new Abstract: Accurate fault location is critical for distribution network reliability. However, increasing distributed energy resource (DER) penetration complicates

Beyond Retrieval: Analytic Memory for Multimodal Agents

arXiv:2607.29440v1 Announce Type: new Abstract: Long-term multimodal memory must support not only retrieving relevant information but also computing over observations accumulated across interactions.

researcharxiv-cs-ai

BLADE: Boundary-Expanded and Layer-Adaptive Dynamic Exit for Efficient LLM Reasoning

arXiv:2607.28966v1 Announce Type: new Abstract: Large language models often improve task performance by generating long reasoning traces, but the resulting computation is frequently wasted on redundan

BWM: A Low-Cost High-Fidelity World Simulator for Robot Learning

arXiv:2607.29302v1 Announce Type: cross Abstract: Reliable robot learning requires a world simulator that can predict action consequences before execution on physical hardware, including risky and fai

Applications

CalibratedRubric: Task-Adaptive Rubric Banks for Open-Ended LLM Evaluation

arXiv:2607.29252v1 Announce Type: cross Abstract: Reliable evaluation of open-ended LLM outputs requires fine-grained rubrics, yet expert curation is costly and difficult to scale. Existing automated

applicationsarxiv-cs-ai

CENDRe: Concept Extraction with Natural Domain Representations

arXiv:2607.29621v1 Announce Type: cross Abstract: Convolutional neural networks (CNNs) are widely used for time-series classification, but their deployment in critical domains requires understanding t

local-aiarxiv-cs-ai

CoDe-SSM: Context-Detail Decoupled State Space Model for Efficient UHD Image Restoration

arXiv:2607.29595v1 Announce Type: new Abstract: Ultra-high-definition (UHD) image restoration must balance the aggregation of spatially recurring degradation cues with the preservation of localized im

local-aiarxiv-cs-cv

Conditioning Tree-Based Diffusions and Flows for Probabilistic Tabular Regression

arXiv:2607.28864v1 Announce Type: cross Abstract: Tree-based diffusion models fit flexible conditional predictive distributions for tabular regression without a neural density estimator, but they inhe

researcharxiv-cs-lg

Tutorials

Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning

arXiv:2607.19345v2 Announce Type: replace-cross Abstract: Large language models that generate step-by-step reasoning traces have achieved strong performance on complex tasks, and extending them to lon

tutorialsarxiv-cs-ai

Cross-Resolution Semantic Learning for Graph Domain Adaptation

arXiv:2607.29365v1 Announce Type: new Abstract: Graph Domain Adaptation (GDA) transfers predictive knowledge from labeled source graphs to unlabeled target graphs under distribution shift. Existing me

researcharxiv-cs-lg

Deconstructing Off-Policy Ratios: Entropy-Scaled Trust Regions for Asynchronous Reinforcement Learning

arXiv:2607.22186v2 Announce Type: replace Abstract: Asynchronous reinforcement learning (RL) accelerates large language model (LLM) post-training by overlapping rollout generation with policy optimiza

local-aiarxiv-cs-ai

Demystifying Entropy-based Selection for Chain-of-Thought Compression in Large Reasoning Models

arXiv:2607.28707v1 Announce Type: new Abstract: Entropy-based pruning has been proposed as an effective method for compressing Chain-of-Thought (CoT) reasoning with negligible accuracy loss. We test t

Dimensionality reduction for homological stability and global structure preservation

model-releasesarxiv-cs-ai

arXiv:2503.03156v4 Announce Type: replace-cross Abstract: We propose DiRe, a force-directed dimensionality reduction framework designed to preserve global structure and homological features while rema

Domain-Division based Progressive Learning for Source-Free Domain Adaptation

arXiv:2607.29202v1 Announce Type: new Abstract: With growing privacy and portability concerns, source-free domain adaptation requires only a source pre-trained model and an unlabeled target domain, al

Dual-Force: Enhanced Offline Diversity Maximization under Imitation Constraints

arXiv:2501.04426v2 Announce Type: replace-cross Abstract: Offline diversity maximization under imitation constraints can transform demonstration data into a set of distinct behavioral policies, improv

safetyarxiv-cs-ai

DuET: Dual Expert Trajectories for Diffusion Image Editing

arXiv:2606.13303v2 Announce Type: replace Abstract: Recent diffusion editors perform diverse instruction-based edits while conditioning on the source image at every denoising step. Yet persistent sour

Dynamics-aware identification of governing equations from sparse and noisy data

arXiv:2607.29036v1 Announce Type: new Abstract: Sparse identification of nonlinear dynamics (SINDy) and PDE functional identification (PDE-FIND) recover parsimonious ordinary and partial differential

ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics

arXiv:2603.11872v3 Announce Type: replace-cross Abstract: Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI sy

agentsarxiv-cs-ai

Fast Rates for Swap-Agnostic Learning of Proper Losses

arXiv:2607.28856v1 Announce Type: new Abstract: Swap-agnostic learning strengthens classical agnostic learning by allowing the comparator to select a different hypothesis on each level set of the lear

Feature Interaction Modeling for Physics-Informed Neural Networks and Neural Operators

arXiv:2607.28762v1 Announce Type: new Abstract: This work embeds feature interaction modules derived from factorization machines (FMs) into physics-informed neural networks (PINNs) and neural operator

researcharxiv-cs-lg