Search: “benchmark”

ImpactHO: Importance-Aware KV Cache Transfer for Multi-User Edge LLM Handover

arXiv:2608.10545v1 Announce Type: cross Abstract: Edge LLMs must preserve inference continuity when a user hands over between edge nodes, requiring key-value (KV) cache transfer to the target node. Ho

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Implicit representations are dead. Long live explicit primitives!

DGX agent

arXiv:2608.10001v1 Announce Type: cross Abstract: Continuous parameterization of medical data has emerged as a powerful paradigm for resolution-independent image representation. While Implicit Neural

model-releasesarxiv-cs-cv

12 Aug 2026

InSight-doc: Agentic Visual Perception for Long-Document Understanding

model-releasesarxiv-cs-cl

arXiv:2608.10628v1 Announce Type: cross Abstract: Long-document understanding often requires reasoning over many visually rich pages, making inference costly and prone to context rot. In this work, we

Introspective Attention Modulation for Safe Text-to-Image Generation

arXiv:2607.14945v2 Announce Type: replace Abstract: State-of-the-art flow based text-to-image (T2I) models exhibit remarkable generative abilities but remain vulnerable to producing unsafe content. Pr

Invertible Logits Transformation for Accuracy-Preserving Post-Hoc Uncertainty Calibration

arXiv:2608.10372v1 Announce Type: new Abstract: Post-hoc calibration aligns a classifier's predicted confidences with its empirical accuracy without retraining. An ideal calibrator should correct nonl

KKL Observer Synthesis for Nonlinear Systems via Physics-Informed Learning

arXiv:2501.11655v3 Announce Type: replace-cross Abstract: This paper proposes a novel learning approach for designing Kazantzis-Kravaris or nonlinear Luenberger (KKL) observers for autonomous nonlinea

LEGO: Leveled Language Gaussian Splatting

arXiv:2608.10057v1 Announce Type: new Abstract: We introduce LEGO for advanced open-vocabulary scene understanding. Beyond basic concept recognition, its core innovation lies in capturing the intrinsi

researcharxiv-cs-cv

Leveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach

arXiv:2602.16481v2 Announce Type: replace Abstract: Causal discovery seeks to uncover causal relations from data, typically represented as causal graphs, and is essential for predicting the effects of

safetyarxiv-cs-ai

Long-Time Trajectory Approximation via SA-NODEs: Model Predictive and Floquet Strategies

arXiv:2608.10738v1 Announce Type: new Abstract: We study the approximation of dynamical systems by semi-autonomous neural ordinary differential equations (SA-NODEs) over long time horizons. For a sing

MAD-HOI: Masked Autoregressive Diffusion for Generating Articulated Hand Object Interactions from Text

arXiv:2608.10162v1 Announce Type: new Abstract: Methods for text-based generation of hand-object interaction (HOI) sequences primarily focus on producing smooth, physically plausible trajectories. A t

MAP-Graph: Provenance-Aware Shared Memory for Multi-Agent Workflows

arXiv:2608.10509v1 Announce Type: new Abstract: Shared memory helps language-model agents reuse information across long workflows, yet relevant evidence may not be admissible for a particular agent or

MD-ProTector: Positioning Multiple Data-Driven Prototypes for LLM-Generated Text Detection

arXiv:2608.10459v1 Announce Type: cross Abstract: As LLM-generated content becomes more sophisticated, detection systems for distinguishing those texts from human-written text must operate at scale wh

Agents

MIRA: Medical Image Reflection for Agentic Diagnosis

arXiv:2608.10827v1 Announce Type: cross Abstract: Medical visual agents can use tools to inspect images and retrieve external knowledge, but indiscriminate tool use may introduce noisy or misleading e

agentsarxiv-cs-ai

More Accurate, Less Human: Gestalt Grouping in Vision Models

arXiv:2608.10195v1 Announce Type: new Abstract: Human vision organizes what it sees into wholes: same-colored points group into series, similar marks cohere into categories, and shapes complete into r

Multimodal Item Parameter Estimation using Simulated Response Probabilitie

arXiv:2608.10154v1 Announce Type: cross Abstract: We present results from reconstructing multiple-choice model (MCM) and three-parameter logistic (3PL) model curves using a fine-tuned multimodal large

Multiplayer Nash Preference Optimization

arXiv:2509.23102v4 Announce Type: replace Abstract: Reinforcement learning from human feedback (RLHF) has emerged as the standard paradigm for aligning large language models with human preferences. Ho

safetyarxiv-cs-ai

Neural Introspection Gating for Adaptive KV-Cache Reuse in Vision-Language-Action Models

arXiv:2608.10824v1 Announce Type: cross Abstract: Vision-Language-Action(VLA) models map camera images and language instructions directly to motor commands through a single autoregressive transformer.

Off-Axis, On Purpose: Where a Transformer Computes Concepts and Why it Does So

arXiv:2608.10251v1 Announce Type: new Abstract: A transformer's answer lives on one axis: the direction its unembedding reads. Its intermediate states largely do not, and that off-axis position is usu

researcharxiv-cs-cl

Optimized Sequential Testing for Binary Ensemble Classifiers

arXiv:2606.15237v1 Announce Type: cross Abstract: Ensemble classifiers are predictive models that combine the results of simpler base models, often by majority vote. A classic example is random forest

Pair-Centric Graph Rewiring for Over-Squashing via Optimal Transport-Guided Communication Alignment

arXiv:2608.10619v1 Announce Type: new Abstract: Message-passing neural networks (MPNNs) often struggle when task-relevant information is distributed across distant regions of a graph, since local prop

safetyarxiv-cs-lg

Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure

arXiv:2606.17441v2 Announce Type: replace-cross Abstract: Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and ex

PEAK: Precise and Persistent Concept Erasure via k-Sparse Autoencoders

arXiv:2608.10985v1 Announce Type: new Abstract: Erasing concepts from large-scale text-to-image (T2I) diffusion models has become increasingly crucial due to the growing concerns over copyright infrin

Post-Hoc Sparse Coding of Latent Communication Between Vision-Language Model Agents

arXiv:2608.10198v1 Announce Type: new Abstract: Latent-space communication allows heterogeneous vision-language model agents to exchange continuous representations without serializing visual and reaso

Pretrained Optimization Model for Zero-Shot Black Box Optimization

arXiv:2405.03728v3 Announce Type: replace-cross Abstract: Zero-shot optimization involves optimizing a target task that was not seen during training, aiming to provide the optimal solution without or

ProTAGAD: A Foundation Model for TAG Anomaly Detection with Decoupled Topological and Textual Prototypes

arXiv:2608.10699v1 Announce Type: cross Abstract: Text-Attributed Graphs (TAGs), endowed with abundant textual content along with topological structures, have emerged as a versatile backbone for real-

Tutorials

Rationale-Guided Learning for Multimodal Emotion Recognition

arXiv:2608.10448v1 Announce Type: new Abstract: Multimodal emotion recognition in conversation (MERC) requires understanding complex interactions between verbal and non-verbal cues. However, most exis

tutorialsarxiv-cs-ai

Reasoning Shortcuts and Value Symmetries: What Symmetry Permits, Architecture Realizes, and Optimization Selects

arXiv:2608.10420v1 Announce Type: new Abstract: Reasoning shortcuts are solutions of a neurosymbolic system's rules that produce correct predictions through unintended concepts. A recent framework of

Applications

REATS: LLM Reasoning-based Ensemble Learning for Adaptive Time Series Forecasting

arXiv:2608.10149v1 Announce Type: new Abstract: Due to the diversity of real-world time series, no single forecasting model consistently dominates across all samples. Ensemble learning addresses this

applicationsarxiv-cs-lg

ReLTEx: Reliable LLM-based Taxonomy Expansion

arXiv:2608.10970v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have demonstrated strong capabilities in generating semantically relevant concepts and relations, maki

Applications

Retrieval-Augmented Vision Foundation Models for Robust Leukemia Cell Classification across Multiple Microscopy Datasets

arXiv:2608.10657v1 Announce Type: cross Abstract: Leukemia cell image classification is challenged by real-world domain shifts from acquisition, staining, illumination, and site protocols, causing sin

applicationsarxiv-cs-cv

Local Ai

Retrieval-Corrected Conformal Prediction for Time Series

arXiv:2608.10553v1 Announce Type: cross Abstract: Conformal prediction (CP) provides distribution-free prediction intervals for fixed forecasters, but its standard calibration procedure is often ineff

local-aiarxiv-cs-ai

SAR2Agri: Learning SAR Intensity Representations for Agricultural Monitoring

arXiv:2608.11142v1 Announce Type: new Abstract: Agricultural monitoring faces unique challenges, arising from the landscape's complex temporal, phenological, and climate dynamics, yet monitoring them

Seeds Before Objectives: Rethinking Evaluation for Low-Resource Garhwali ASR

model-releasesarxiv-cs-cl

arXiv:2608.10670v1 Announce Type: new Abstract: At corpus sizes typical of low-resource dialects, single-run comparisons can yield gains that do not replicate. We show this for Garhwali, an under-reso

Self-Correcting Long-Horizon Search Agents via Tree-Structured Memory

arXiv:2608.10676v1 Announce Type: new Abstract: Large language model (LLM)-based search agents answer questions through multi-step interactions with external environments. However, providing complete

Self-Geometry: GT-Free and Plug-and-Play Test-Time Adaptation for Geometrically Consistent 3D Vision Foundation Models

arXiv:2608.10708v1 Announce Type: new Abstract: Recent Vision Foundation Models (VFMs) predict depth, camera pose, and pointmap in a single forward pass without per-scene optimization, achieving stron

researcharxiv-cs-cv

SinD 2.0: A Multi-City UAV Dataset with Semantic Risk Annotations for SOTIF-Oriented Safety Validation at Signalized Intersections

model-releasesarxiv-cs-ro

arXiv:2607.16943v2 Announce Type: replace Abstract: Safety validation at signalized intersections remains a critical bottleneck for the deployment of autonomous driving systems (ADS), as these scenari

Agents

SKILLER: Language-Level Reinforcement Learning for Reusable Skill Extraction in Small Language Models

arXiv:2608.10538v1 Announce Type: new Abstract: Agent skills represent a standardized format for packaging procedural knowledge and domain expertise, serving within agent harness systems as an essenti

agentsarxiv-cs-ai

Static in Frames, Dynamic in Events: Rethinking Features in Event Cameras as Motion Cues

arXiv:2608.11075v1 Announce Type: new Abstract: Event cameras capture intensity changes asynchronously with high temporal resolution, requiring novel preprocessing methods for downstream tasks. Unlike

StreamFlow: Dynamic Memory Flows for Streaming Video Understanding

arXiv:2608.10949v1 Announce Type: cross Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to preserve relevant evidence from continuously evolving streams under

researcharxiv-cs-cl

TACTICL: Task-Aware Compression of Tabular ICL Models

arXiv:2608.10837v1 Announce Type: cross Abstract: The strong performance of foundation models for tabular tasks comes at substantial inference costs. Distilling models into task-specific architectures

The Gaussian-Multinoulli Restricted Boltzmann Machine: A Potts Model Extension of the GRBM

arXiv:2505.11635v2 Announce Type: cross Abstract: Many real-world tasks, from associative memory to symbolic reasoning, benefit from discrete, structured representations that standard continuous laten

The Hidden Puppet Master: Predicting Human Belief Change in Manipulative LLM Dialogues

arXiv:2603.20907v5 Announce Type: replace Abstract: As users increasingly turn to LLMs for practical and personal advice, they become vulnerable to subtle steering toward hidden incentives misaligned

safetyarxiv-cs-cl

Local Ai

The Kuramoto Neural Operator: Learning to Solve PDEs via Coupled Oscillator Dynamics

arXiv:2608.10234v1 Announce Type: cross Abstract: Operator learning is a rapidly advancing area of computational science. It is particularly well suited to problems where a partial differential equati

local-aiarxiv-cs-lg

Towards Color-Faithful Low-Light Image Enhancement via Adaptive Color Debiasing and Saturation Rectification

arXiv:2608.10512v1 Announce Type: new Abstract: Low-light imaging often introduces color bias caused by the low signal-to-noise ratio and the image formation process. Although recent low-light image e

safetyarxiv-cs-cv

Towards Efficient Reasoning in LLM-Based Recommender Systems via Model Merging

arXiv:2608.10447v1 Announce Type: cross Abstract: Large language model-based recommender systems are increasingly adopting slow-thinking models that generate step-by-step reasoning before making predi

TrAC: Trace-Conditioned Answer Consistency for Efficient Uncertainty Quantification in LLMs

arXiv:2608.00422v2 Announce Type: replace Abstract: Large language models (LLMs) can generate fluent reasoning traces that nevertheless lead to incorrect answers, making response-level uncertainty est

TRACE: Trustworthy Retrieval-Augmented Conversational Engine

arXiv:2608.10176v1 Announce Type: new Abstract: Public service chatbots are expected to deliver recommendations from an underlying public service directory, while also making sure that the recommendat

Uncertainty-Aware Ensemble Deep Randomized Neural Networks for Classification

arXiv:2608.10007v1 Announce Type: cross Abstract: The current state-of-the-art (SOTA) deep randomized neural networks, such as deep Random Vector Functional Link (dRVFL) and ensemble deep RVFL (edRVFL