Search: “benchmark”

Glance, Scrutinize, and Think: Advancing Video Anomaly Detection from Training-Free to Agentic Reasoning

arXiv:2608.11260v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) aims to identify anomalous events and localize their temporal intervals. Existing approaches exhibit a 'when-what' dissoci

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Model Releases

Gloss-Free Representation Learning for Cross-Dataset Sign Spotting

DGX agent

arXiv:2608.11332v1 Announce Type: new Abstract: Sign-language research for resource-constrained languages is often limited by the cost of dense linguistic labels such as glosses, temporal boundaries,

model-releasesarxiv-cs-cl

13 Aug 2026

Graph-Structured Rubrics: Compiling Rubrics into Typed Evaluation Graphs for LLM Judges

arXiv:2608.12097v1 Announce Type: new Abstract: Rubric-based evaluators commonly treat rubrics as prompt context or flat criteria: they specify what to judge but leave criterion composition implicit,

HCGRec: Hint-Conditioned Generative Recommendation with Semantic IDs

arXiv:2608.11980v1 Announce Type: cross Abstract: Semantic-ID generative recommenders represent each item as a short sequence of discrete semantic tokens and predict the next item by autoregressively

Herding End-to-End Autonomous Driving via Neuro-Symbolic Safety Guards

arXiv:2608.11451v1 Announce Type: cross Abstract: Modern end-to-end driving agents can achieve high average performance yet still violate basic traffic rules that a human driver would never miss. The

Local Ai

High-dimensional Multi-objective Bayesian Optimization with Learned Variable Interactions

arXiv:2608.11713v1 Announce Type: cross Abstract: Multi-objective Bayesian optimization (MOBO) is effective in identifying the Pareto fronts for expensive black-box problems. However, most current MOB

local-aiarxiv-cs-ai

How Can Driving World Models Do Counterfactual Prediction?

arXiv:2608.11601v1 Announce Type: new Abstract: Driving world models are often interpreted as counterfactual simulators for observed driving episodes: given a factual driving log, they are asked what

How China-Origin Vision-Language Models Move from Refusal to Reframing in State Alignment

arXiv:2608.11816v1 Announce Type: cross Abstract: State-aligned distortion has been documented in China-origin text-based large language models (LLMs), but whether, and in what form, it arises in mult

How to Spend Your Oracle Budget: Practical Guidance for Protein Structure Prediction Models

arXiv:2608.12192v1 Announce Type: new Abstract: Foundation models for protein structure prediction remain unreliable on certain targets. External oracles can flag and correct these failures, but biolo

HUGIN: Enhancing Vision-Language Planning for Autonomous Logistics Sorting

arXiv:2608.11692v1 Announce Type: new Abstract: Autonomous logistics sorting systems (ALSS) are an important industrial application of embodied AI, which requires joint planning over spatially disjoin

Hybrid Gated Attention

arXiv:2608.11805v1 Announce Type: new Abstract: Gated attention is an effective approach to mitigate attention sinks and enhance the representational capacity of attention. To further extend its effec

researcharxiv-cs-cl

Applications

Hybrid-LUT: Channel-Aware Hybrid Lookup Table and Filtering for Efficient Image Denoising

arXiv:2608.11646v1 Announce Type: new Abstract: Lookup table (LUT)-based image denoising methods have attracted increasing attention due to their high efficiency and hardware-friendly properties. Howe

applicationsarxiv-cs-cv

HYDRA: Hyperbolic Dynamic Representation Architecture for Kolmogorov-Arnold Networks

arXiv:2608.12194v1 Announce Type: cross Abstract: Kolmogorov-Arnold Networks (KANs) enhance nonlinear function approximation by replacing scalar weights with learnable univariate functions. However, a

HyperFix: Combinatorial Nonlinear Correction for Task Vector Merging

arXiv:2608.11499v1 Announce Type: cross Abstract: Task vectors enable model merging without joint retraining. In practice, the subset of task vectors to be merged may vary, but many existing methods u

InfraBench: Evaluating Infrastructure Agents Across Layers, Lifecycle, and Risk

arXiv:2608.11234v1 Announce Type: new Abstract: Managing modern computing infrastructure has become a steadily harder problem due to the ever-increasing complexity. Recent advances in AI agents create

Applications

JAPE: Joint Anomaly Prediction and Intrinsic Explanation in Multivariate Time Series

arXiv:2608.11801v1 Announce Type: new Abstract: Multivariate time-series anomaly prediction aims to identify whether and when anomalies will occur over a future horizon from historical observations. E

applicationsarxiv-cs-lg

Latent variable models for simultaneous EOV identification and removal in population-based SHM

arXiv:2608.11995v1 Announce Type: cross Abstract: The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM).

Learning from Multimodal Pseudo-Labels for Robust Open-Vocabulary Instance and Panoptic Segmentation

arXiv:2608.11681v1 Announce Type: cross Abstract: This work addresses the challenge of open-vocabulary instance segmentation (OVIS) and open-set panoptic segmentation (OSPS), which aim to recognize bo

Learning with Bilevel-Minimax Optimization for Efficient and Reliable Transfer Attacks

arXiv:2608.11815v1 Announce Type: cross Abstract: Transfer-based adversarial attacks craft adversarial examples using surrogate models to mislead black-box victim models. Beyond perturbation generatio

researcharxiv-cs-cv

LiveAnimate: Stable Long-Form Streaming Human Animation in Real-Time

arXiv:2608.11745v1 Announce Type: new Abstract: Pose-driven human animation synthesizes a video of a target person from a single reference image and a driving pose stream. Real-time generation is esse

Local Cluster Cardinality Estimation for Adaptive Mean Shift

arXiv:2508.12450v2 Announce Type: replace Abstract: This article presents an adaptive mean shift algorithm in which every parameter used at a point is derived from that point's own distance distributi

Locating and Controlling Implicit Personalization in Large Language Models

arXiv:2608.11735v1 Announce Type: cross Abstract: Large language models (LLMs) often shift their outputs in response to implicit demographic cues even when users never state a demographic identity. Pr

Long-Horizon Forecasting of Complete Financial Statements with Forma

arXiv:2608.11327v1 Announce Type: new Abstract: Specialist training beats generalist scale when forecasting financial statements. To our knowledge, no prior work jointly forecasts complete financial s

Tutorials

LookBack: Where and How to Score LVLM Responses via Visual Reference Usage

arXiv:2608.11847v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) integrate visual perception with language generation, enabling responses that span image understanding and comple

tutorialsarxiv-cs-ai

LoongReflect: Boosting Long-Horizon Reflection in Search Agents via Global Perspective Distillation

arXiv:2608.11967v1 Announce Type: cross Abstract: Large language model agents increasingly rely on long-horizon reasoning to solve complex tasks involving planning, tool use, and memory. A critical ca

M-Net: Integrating Spectral Features and Physical Field Operators into Deep Learning for Medical Image Segmentation

arXiv:2608.12196v1 Announce Type: cross Abstract: Purpose: Deep learning-based medical image segmentation has achieved remarkable success, yet purely data-driven approaches often fail to exploit the r

Local Ai

Map-Det3D: Metric Feed-Forward 3D Reconstruction Prior for Multi-view 3D Object Detection from Streaming Inputs

arXiv:2608.12179v1 Announce Type: new Abstract: Metric 3D object detection is a core capability for embodied agents, yet most reliable systems lean on depth sensors, trading away cost, power, and inte

local-aiarxiv-cs-cv

Measuring Browser Webcam Gaze Honestly: A Capture-Clock Methodology and Open Reference Implementation

arXiv:2608.11566v1 Announce Type: cross Abstract: Browser-based webcam gaze trackers are increasingly used for crowd-scale data collection and in clinical settings where lab eye trackers are impractic

Mechanism Design for Generative Engines: From Exploitation toward Win-Win Outcomes

arXiv:2608.11390v1 Announce Type: new Abstract: Generative engines are reshaping the web ecosystem by making citations a key mechanism for allocating attention, attribution, and downstream value. This

researcharxiv-cs-lg

MicroAUNet: Boundary-Enhanced Multi-scale Fusion with Knowledge Distillation for Colonoscopy Polyp Image Segmentation

arXiv:2511.01143v2 Announce Type: replace-cross Abstract: Early and accurate segmentation of colorectal polyps is critical for reducing colorectal cancer mortality, which has been extensively explored

MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning

arXiv:2608.11749v1 Announce Type: cross Abstract: Multi-objective optimization (MOO) has demonstrated significant success in multi-task learning by mitigating task conflicts through gradient manipulat

Multi-Agent Embodied Autonomous Driving: From V2X Information Exchange to Shared World Models

arXiv:2606.13840v2 Announce Type: replace-cross Abstract: Autonomous driving is shifting from isolated vehicle intelligence toward multi-agent embodied systems that share perception, infer intent, and

safetyarxiv-cs-cv

MuseCritic: Learning Multi-Aspect Song Rewards through Natural-Language Aesthetic Critiques

model-releasesarxiv-cs-cl

arXiv:2608.11755v1 Announce Type: cross Abstract: Long-form song generation models continue to improve in duration, structural integrity, and acoustic complexity, making reliable aesthetic rewards inc

NAE: Normalizing AutoEncoder

arXiv:2608.12084v1 Announce Type: new Abstract: We consider the setting of Normalizing flows with approximate inverses, an established paradigm spanning both full-dimensional (d=D) and bottleneck (d<D

safetyarxiv-cs-lg

NetlistBench: Evaluating LLM Reliability in SPICE Netlist Recognition and Manipulation

arXiv:2608.12197v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in circuit design workflows, yet their reliability on simulator-facing SPICE netlist recognition an

ODE-Based Transformer Decoders for Iterative Sign Language Translation

model-releasesarxiv-cs-cl

arXiv:2608.11352v1 Announce Type: new Abstract: Sign language translation has achieved strong results with Transformer architectures, yet recent improvements largely rely on scaling model capacity at

One Frozen Simulator Is Not Enough: Simulator Collapse in Multi-Agent RL

arXiv:2608.12253v1 Announce Type: cross Abstract: Multi-agent reinforcement learning for human-AI interaction typically relies on a single large language model to simulate user behavior. We show that

OpenVE-3M: A Large-Scale High-Quality Dataset for Instruction-Guided Video Editing

arXiv:2512.07826v3 Announce Type: replace Abstract: The quality and diversity of instruction-based image editing datasets are continuously increasing, yet large-scale, high-quality datasets for instru

out of curiosity, i tasked fable to figure this thing out and it looks like the 'saas killer' is done. ▲ it maxed out Fable 5 + used most of…

out of curiosity, i tasked fable to figure this thing out and it looks like the 'saas killer' is done. ▲ it maxed out Fable 5 + used most of Codex limits ▲ most of the work was done within 45h session

model-releasesswyx--x

Patch-based Memory Gate Model in Time Series Foundation Model

arXiv:2509.18751v4 Announce Type: replace Abstract: Recently reconstruction-based deep models have been widely used for time series anomaly detection, but as their capacity and generalization capabili

Local Ai

Predicting Functions, Not Features: KANs with Function-Space Joint-Embedding Predictive Learning for Medical Image Segmentation

arXiv:2608.12050v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) introduce explicit functional representations by parameterizing each network edge as a learnable univariate function.

local-aiarxiv-cs-cv

Probably Approximately Correct Maximum A Posteriori Inference

arXiv:2601.16083v2 Announce Type: replace-cross Abstract: Computing the conditional mode of a distribution, better known as the maximum a posteriori (MAP) assignment, is a fundamental task in probabil

Qwen-MusicAVQA-7B: A Multimodal Model for Music Audio-Visual QA

arXiv:2608.11329v1 Announce Type: cross Abstract: A common approach to adding audio to a vision-language model is to train or adapt a large omni-modal system. We show that a lightweight alternative ca

Reducing Per-Sample Interference in Stochastic Optimization

arXiv:2607.16261v2 Announce Type: replace-cross Abstract: Modern optimizers combine gradients from the current mini-batch with historical optimization state, such as momentum or adaptive moments. Whil

Reinforcement Learning based DBMS Buffer Pool Auto-Tuning for Optimal Memory Utilization

arXiv:2608.11239v1 Announce Type: cross Abstract: Administering Database Management Systems (DBMS) instances requires Database Administrators (DBA) to balance performance in terms of Service Level Agr

Reliable Inference in Edge-Cloud Model Cascades via Conformal Alignment

arXiv:2510.17543v3 Announce Type: replace Abstract: Edge intelligence enables low-latency inference via compact on-device models, but assuring reliability remains challenging. We study edge-cloud casc

Representation Finetuning for Continual Learning

arXiv:2603.11201v3 Announce Type: replace-cross Abstract: The world is inherently dynamic, and continual learning aims to enable models to adapt to ever-evolving data streams. While pre-trained models

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision

arXiv:2608.11564v1 Announce Type: new Abstract: Depth estimation from thermal images is highly valuable for robotic applications in adverse conditions, such as nighttime and rainy weather. Recent stud