Search: “evaluation”

DAVET: Denoising-Aware Visual Evidence Trajectory Allocation for Diffusion Vision-Language Models

arXiv:2608.01821v1 Announce Type: new Abstract: Diffusion vision-language models (dVLMs) iteratively denoise masked responses while conditioning each denoising step on visual evidence, making visual c

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Deep Learning CNN and Recurrence Analysis for Alpha Gamma EEG Biomarkers in Fragile X Syndrome

DGX agent

arXiv:2608.00835v1 Announce Type: cross Abstract: Fragile X Syndrome (FXS) is a neurodevelopmental disorder caused by reduced expression of fragile X mental retardation protein (FMRP), leading to disr

tutorialsarxiv-cs-cv

4 Aug 2026

Demystifying When and Why VLAs Fail in Contact-Rich Tasks and How to Fix Them

arXiv:2608.01402v1 Announce Type: new Abstract: We address the problem of understanding when and why Vision-Language-Action models struggle with contact-rich manipulation tasks that require precise ph

safetyarxiv-cs-ro

Deployment-Ready UWB Localization for Industrial Ground Robots with Automatic Anchor Calibration and Terrain-Aware Fusion

model-releasesarxiv-cs-ro

arXiv:2607.15807v2 Announce Type: replace Abstract: Ultra-Wideband (UWB) ranging has become a viable option for industrial Autonomous Mobile Robot (AMR) localization due to improved accuracy and low c

Detail Continuation over a Trustworthy Coarse Scale for Autoregressive Super-Resolution

arXiv:2608.01823v1 Announce Type: new Abstract: Hallucination remains a persistent challenge in generative super-resolution (GSR), where reconstructed results may contain visually plausible yet weakly

Tutorials

DexMani: Human-Derived Manipulability Guidance for Dexterous Rotation

arXiv:2608.00554v1 Announce Type: cross Abstract: Dexterous object rotation is a sequential contact problem: each support, release, and re-contact decision must both produce the desired object motion,

tutorialsarxiv-cs-cv

Diffusion Policy with Behavioral Advantage Correction for Offline Reinforcement Learning

arXiv:2608.02332v1 Announce Type: new Abstract: In offline reinforcement learning (RL), the distribution shift between behavioral data and the learned policy can lead to erroneous Q-value estimation,

DiffusionGemma Technical Report

model-releasesarxiv-cs-cl

arXiv:2608.00146v1 Announce Type: new Abstract: We introduce DiffusionGemma, an experimental open-weight language model that uses discrete diffusion to generate text at exceptionally high speed. Rathe

Direct and Adaptable Mesh-Gaussian Scene Reconstruction from Multi-View Images

arXiv:2405.06945v4 Announce Type: replace Abstract: Jointly recovering explicit surface geometry and high-quality appearance from multi-view images remains challenging. This capability is essential fo

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models

arXiv:2608.01263v1 Announce Type: new Abstract: On-policy distillation (OPD) samples trajectories from the current student policy and minimizes token-level divergence between student and teacher next-

Distributional Matching for Vector Quantization: A Unified Theoretical and Empirical Framework

arXiv:2607.15933v2 Announce Type: replace Abstract: The effectiveness of modern visual representation learning and autoregressive models critically depends on vector quantization (VQ), which discretiz

Do Maps Still Matter for Machines: Revisiting the Role of Choropleth Maps in Foundation Model Spatial Understanding

arXiv:2607.17999v2 Announce Type: replace-cross Abstract: Spatial understanding is crucial for foundation models (FMs), and maps have long helped humans organize and reason about geographic informatio

Tutorials

Does Machine 'know' interpersonal pragmatics? Evidence from MARBERT's learning of emoji pragmatics in Arabic digital discourse

arXiv:2608.01174v1 Announce Type: new Abstract: This study examines Transformer-based models' ability to learn emoji pragmatics in Arabic digital discourse (ADD), providing evidence from MARBERT's beh

tutorialsarxiv-cs-cl

Don't Offer What Can't Be Done: Deterministic Executability Gating for LLM Skill Selection at Scale

arXiv:2608.01050v1 Announce Type: cross Abstract: Production LLM agents that select from large skill libraries face a limitation that semantic relevance alone cannot resolve: a skill may match a user'

applicationsarxiv-cs-cl

Douyin Multimodal Embedding Model Technical Report

arXiv:2608.02148v1 Announce Type: cross Abstract: Multimodal representation learning is a cornerstone of modern AI. By encoding multimodal queries and targets into vectors, it powers industrial search

applicationsarxiv-cs-cl

DriveCode: Domain Specific Numerical Encoding for LLM-Based Autonomous Driving

arXiv:2603.00919v3 Announce Type: replace Abstract: Large language models (LLMs) have shown great promise for autonomous driving. However, discretizing numbers into tokens limits precise numerical rea

DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration

arXiv:2608.01452v1 Announce Type: cross Abstract: Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that a

DynamicWAM: Dual-Path Motion Conditioning for World-Action Models in Dynamic Manipulation

arXiv:2608.00793v1 Announce Type: new Abstract: Dynamic manipulation requires robots to infer target motion and respond promptly, yet existing World-Action Models (WAMs) typically condition only on th

applicationsarxiv-cs-ro

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers

arXiv:2607.17244v2 Announce Type: replace Abstract: Longitudinal T cell receptor repertoires contain signals of clonal expansion, contraction, disappearance, and reappearance after immune perturbation

Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs

arXiv:2511.00382v2 Announce Type: replace-cross Abstract: Organizations increasingly adapt Large Language Models (LLMs) from public repositories such as HuggingFace to downstream tasks. Prior work sho

Local Ai

Efficient nonlinear flame response modeling for propulsion thermoacoustic analysis using limited numerical data

arXiv:2409.05885v2 Announce Type: replace Abstract: Characterizing nonlinear flame response is critical for predicting thermoacoustic instabilities in propulsion combustors, yet obtaining a comprehens

local-aiarxiv-cs-lg

Ego2Robot: Scalable Robot Data Synthesis from Egocentric Human Data

arXiv:2608.02580v1 Announce Type: new Abstract: Learning generalizable robot manipulation policies requires large-scale and diverse demonstration data. Egocentric human manipulation videos offer rich

researcharxiv-cs-ro

EgoIntent: A Pre-Outcome Micro-Step Benchmark for Understanding What, Why, and Next

arXiv:2603.12147v2 Announce Type: replace Abstract: Egocentric video provides a natural modality for studying human behavior, but conventional visual understanding captures mainly observable scenes, o

Enhancing Visual Perception in Foggy Conditions via Multiclass Fog Density Modeling

arXiv:2608.01572v1 Announce Type: new Abstract: Autonomous driving (AD) systems have advanced rapidly over the past decade; however, robust perception under adverse weather conditions remains a major

EOVSAM: Efficient Open-Vocabulary Segmentation with SAM 3 in One Pass

arXiv:2608.02284v1 Announce Type: new Abstract: Open-vocabulary segmentation identifies and segments objects from arbitrary textual descriptions. SAM 3 supports noun-phrase-guided segmentation and ach

EulerLoRA: Rank-Driven Jump Dynamics for Calibrated Parameter-Efficient Fine-Tuning

arXiv:2608.01142v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) enables parameter-efficient fine-tuning, but standard LoRA produces a single deterministic model and does not directly suppor

Event ActivityNet: A Large-Scale Simulated-Event Benchmark for Untrimmed Action Understanding

arXiv:2608.01948v1 Announce Type: new Abstract: Long-horizon event-based action understanding remains underexplored because existing datasets largely comprise short, trimmed clips, while collecting na

Local Ai

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents

arXiv:2608.01359v1 Announce Type: new Abstract: Outcome-based reinforcement learning enables search-augmented language agents to learn from verifiable final answers, but its trajectory-level credit ca

local-aiarxiv-cs-cl

Explainable Multimodal AI for Adaptive Calibration of Archaeological Sensing Workflows

arXiv:2608.00074v1 Announce Type: new Abstract: This paper presents a multimodal machine-learning framework for calibration monitoring, quality assessment, and adaptive acquisition support in archaeol

Exploiting Intrinsic Duality for Multi-Hop Question Generation

arXiv:2608.00712v1 Announce Type: new Abstract: Multi hop question generation (MQG) aims to generate questions from multiple given documents and target answers, whereas question answering (QA) focuses

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Extended Field of View Analysis for VideoGAN-based Trajectory Generation

arXiv:2608.02289v1 Announce Type: new Abstract: Realistic and diverse trajectory generation is central to enabling higher levels of vehicle automation. While rule-based and classical learning-based me

Extended KAFR: A kinematic-adaptive paradigm for the efficient analysis of surgical video

arXiv:2608.01058v1 Announce Type: new Abstract: Artificial Intelligence is increasingly applied to surgical video analysis for phase segmentation, skill assessment, and workflow optimization. A key ch

FactorJEPA: Factorizing Monolithic Futures into Layout-Agent-Interaction Channels for Crowded and Chaotic Global South Urban Worlds

arXiv:2608.01049v1 Announce Type: cross Abstract: World models have attracted significant attention for their ability to capture and predict the structure and dynamics of the physical world. In this e

FastGFDs: Efficient Validation of Graph Functional Dependencies with Desbordante

arXiv:2608.02321v1 Announce Type: cross Abstract: Graph functional dependencies (GFD) are a recently-developed concept aimed at capturing both topological structures in graphs and functional dependenc

FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting

arXiv:2608.01290v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) such as Chronos have demonstrated strong forecasting capabilities across domains, yet adapting them to institution

Fenced Citation-Context Retrieval for Case Law: Temporal Leakage and Degree Control Across Two Jurisdictions

arXiv:2607.17142v3 Announce Type: replace-cross Abstract: Prior case retrieval (PCR) aims to identify the precedent cases relevant to the facts of a query case. Incoming citation context, the text wit

researcharxiv-cs-cl

Few-Shot Biomedical Relation Extraction with Large Language Models: A Viable Alternative to Supervised Learning?

arXiv:2606.15412v2 Announce Type: replace Abstract: Biomedical relation extraction (BioRE) is a key step in transforming biomedical literature into structured knowledge. Most existing approaches rely

researcharxiv-cs-cl

FinHardBench: Can LLMs Generate Latency-Aware Hardware for Financial Computing?

model-releasesarxiv-cs-cl

arXiv:2608.00909v1 Announce Type: new Abstract: Can large language models generate not just correct, but fast hardware? This paper investigates the question in financial FPGA design, where 5-10 nanose

Finite-Probe Total-Variation Certificates for Finite-Basis Drifting Models

arXiv:2608.01547v1 Announce Type: cross Abstract: Drifting objectives compare a target and model distribution through a vector field observed noisily at finitely many locations. We ask what distributi

From AI Weather Prediction to Infrastructure Resilience: A Real-Time Correction-Downscaling Framework for Tropical Cyclone Impact Forecasting

arXiv:2603.12828v2 Announce Type: replace-cross Abstract: This paper addresses a missing capability in infrastructure resilience: turning fast, global AI weather forecasts into asset-scale, actionable

From Digital to Physical Reservoir Computing: Co-Optimizing Soft Robotic Reservoirs via Dynamics Matching

arXiv:2608.00484v1 Announce Type: cross Abstract: Soft robotic substrates are promising for Physical Reservoir Computing (PRC) because their compliant nonlinear dynamics can provide temporal memory, h

From fragmented data to actionable design: Physics-calibrated learning for plastic upcycling

arXiv:2608.02402v1 Announce Type: new Abstract: Thermochemical upgrading of plastic waste is a key upcycling pathway, yet the experimental literature is fragmented by heterogeneous conditions and inco

From Pixels to PCells: A Neurosymbolic Approach to Photonic Component Creation

arXiv:2608.00084v1 Announce Type: new Abstract: We present PixCell, a neurosymbolic system in which multimodal agents convert a visually presented photonic component into a parametric program over a s

Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction

arXiv:2608.01202v1 Announce Type: new Abstract: Fruit ripeness prediction (FRP) is a classification-based agricultural computer vision task that has attracted much attention, thanks to its wide-rangin

applicationsarxiv-cs-cv

FusionRS: A Large-Scale RGB-Infrared-Style Remote Sensing Dataset for Cross-Modal Vision-Language Learning

arXiv:2606.17020v2 Announce Type: replace Abstract: Remote sensing vision-language models have advanced Earth observation, but available large-scale vision-language resources remain RGB-centered, leav

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GAPSL: A Gradient-Aligned Parallel Split Learning over Data-Heterogeneous Edge Computing Systems

arXiv:2603.18540v2 Announce Type: replace Abstract: The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge dev

GenTrack: Physical Alignment for Robot-Native Motion Generation and Zero-Shot Humanoid Tracking

arXiv:2608.01410v1 Announce Type: cross Abstract: General-purpose humanoid trackers can execute diverse references, but their zero-shot coverage depends on large embodied corpora that are costly to ex

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GeoCore-9B: Towards Geo-Aware Generative Foundation Models in Earth Observation

arXiv:2608.01896v1 Announce Type: new Abstract: Existing generative models for earth observation (EO) predominantly rely on fine-tuning natural image priors, which limits their scalability and introdu