Search: “benchmark”

CoDiR: Confidence-Guided Diffusion Refinement for Semi-Supervised Histopathology Segmentation

model-releasesarxiv-cs-cv

arXiv:2608.11807v1 Announce Type: new Abstract: Semi-supervised histopathology segmentation is challenging due to scarce annotations and unreliable pseudo-labels in ambiguous gland regions. To address

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Commonsense on Demand: Generating and Selectively Integrating Commonsense Knowledge for Natural Language Inference

DGX agent

arXiv:2507.15100v3 Announce Type: replace-cross Abstract: Natural Language Inference (NLI) determines whether a premise entails, contradicts, or is neutral with respect to a hypothesis. The task is of

model-releasesarxiv-cs-ai

13 Aug 2026

Context Blindness in DPO: Mitigating Object Hallucination in MLLMs via Context-Calibrated Preference Optimization

arXiv:2608.12158v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made rapid progress, yet they still exhibit object hallucination, generating plausible but incorrect descr

researcharxiv-cs-cv

Continuous-Latent Predictive Modeling with Semantic Alignment for EEG-Language Foundation Models

arXiv:2608.11656v1 Announce Type: new Abstract: Recent advances in EEG foundation models have demonstrated the potential of large-scale pretraining to enable generalizable neural decoding across subje

safetyarxiv-cs-lg

CoQui: A Coordinate-Conditioned Quantum Implicit Generative Adversarial Network for End-to-End Image Generation

arXiv:2608.11884v1 Announce Type: cross Abstract: Quantum generative adversarial networks (QGANs) have attracted increasing attention for image generation using parameterized quantum circuits. Existin

CORE-3D: Context-aware Open-vocabulary Retrieval by Embeddings in 3D

arXiv:2509.24528v4 Announce Type: replace-cross Abstract: Object retrieval from a scene has become a new trend of research due to its numerous applications. Recent approaches achieve zero-shot, open-v

CTBench: Evaluating Troubleshooting Capabilities of AI Agents in Realistic Telecom Network Operations

arXiv:2608.12002v1 Announce Type: new Abstract: Agents are increasingly considered for automating network operations and maintenance, where engineers must diagnose network faults, optimize configurati

Detecting Explanatory Insufficiency in Learned Representations: A Framework for Representational Vigilance

arXiv:2606.13172v3 Announce Type: replace Abstract: Learned representations are central to modern machine learning and are typically evaluated through predictive performance, robustness, uncertainty e

local-aiarxiv-cs-lg

Diffuse to Compress: Leveraging Diffusion LMs for Lossless Compression

arXiv:2608.11249v1 Announce Type: cross Abstract: We study the problem of lossless text compression, motivated by the rapid growth in the collection and storage of digital textual data - including pla

Distillation of Foundation Models for Time-dependent PDEs

arXiv:2608.11937v1 Announce Type: new Abstract: Foundation models for time-dependent partial differential equations (PDEs) are trained on large and diverse collections of physical systems and can gene

local-aiarxiv-cs-lg

Distractor-Aware Video Object Segmentation

model-releasesarxiv-cs-cv

arXiv:2608.11835v1 Announce Type: new Abstract: Semi-supervised video object segmentation is a challenging task that aims to segment a target throughout a video sequence given an initial mask at the f

Do Influence Tactics Matter? Investigating Prompt Framing Effects in LLM Code Generation

arXiv:2608.11513v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into software engineering workflows, helping developers write, debug, test, and maintain code

Do You See What You Draw? A Semantic Closed-Loop Framework for Holistic Evaluation of Unified Multimodal Models

arXiv:2608.11907v1 Announce Type: cross Abstract: As Large Vision-Language Models increasingly aim to integrate visual generation and understanding within a single parameter space, evaluating such str

DreamFly: Causal Memory and Receding-Horizon Diffusion Planning for Aerial Vision-Language Navigation

arXiv:2608.12308v1 Announce Type: cross Abstract: Aerial vision-language navigation (VLN) requires an embodied agent to integrate visual evidence over time, plan future actions, and determine when it

DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation

arXiv:2507.14267v2 Announce Type: replace Abstract: Large language model (LLM) agents can execute long-horizon scientific workflows, but their numerical outputs are difficult to trust: agents lose con

Drift and Dependence: Layer-wise Information-Theoretic Bounds for Replay-Based Continual Learning

model-releasesarxiv-cs-lg

arXiv:2608.11690v1 Announce Type: new Abstract: Continual learning must absorb new tasks without erasing old ones, and replay---mixing a small buffer of past examples into current training---is among

Dual Anchors, Do It Better: Hierarchical Group Merging for Zero-Shot Anomaly Detection

arXiv:2608.11933v1 Announce Type: new Abstract: Zero-shot anomaly detection (ZSAD) aims to identify anomalies in unseen domains, a setting that is particularly critical for industrial and medical appl

safetyarxiv-cs-cv

Dual-Primal Graph VAEs for Noisy Label Aggregation

arXiv:2608.11473v1 Announce Type: new Abstract: Inferring the ground-truth from noisy crowdsourced labels is an important theoretical and practical problem. Neural network-based methods offer an alter

researcharxiv-cs-lg

Dueling Deep Q-Learning for Intrusion Detection

model-releasesarxiv-cs-lg

arXiv:2608.11291v1 Announce Type: cross Abstract: Intrusion detection systems (IDS) and automated systems for detecting and reporting cyber threats, are commonly handled via supervised machine learnin

EGM-Det: Entropy-Guided Multimodal Adaptive Fusion for UAV RGB-IR Object Detection

arXiv:2608.11685v1 Announce Type: new Abstract: Joint use of RGB and infrared (IR) imagery can improve UAV-view object detection, but most existing methods fuse multimodal features with static or fixe

local-aiarxiv-cs-cv

ExRole: From Team Trajectories to Executable Roles in Multi-Agent Language Models

arXiv:2608.11949v1 Announce Type: new Abstract: Roles provide an interpretable interface for organizing language-model agents, yet most multi-agent systems treat them as hand-written prompt labels dis

Faithful, Sufficient and Understandable: Rethinking Graph Counterfactual Explanations via Discrete Diffusion Inversion

arXiv:2608.12083v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) achieve strong predictive performance on graph-structured data across domains such as chemistry, biology, and network ana

Hardware

FLARE++: Low-rank attention with dynamic attention routing

arXiv:2608.11519v1 Announce Type: new Abstract: Full self-attention is a strong token mixer for PDE surrogates on irregular domains, but its quadratic cost limits its use on high-resolution problems.

hardwarearxiv-cs-lg

FM-LLM: A frequency-enhanced mixture-of-experts framework for adapting LLMs to time series forecasting

arXiv:2608.11623v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have spurred cross-modal solutions for time-series forecasting. However, existing methods rely heavily

Forward Trajectory Steering for Hamilton-Jacobi Reachability Analysis

arXiv:2608.11480v1 Announce Type: cross Abstract: Hamilton-Jacobi (HJ) reachability provides a mathematically rigorous framework for safe control of dynamical systems, but its practical application is

safetyarxiv-cs-lg

FunnelCausalNet: Funnel-aware Joint Conversion-Revenue Uplift for Multi-tier Coupon Allocation

arXiv:2608.11675v1 Announce Type: new Abstract: Coupon campaigns seek to lift both conversion and revenue, but gross merchandise value (GMV) follows a deterministic funnel from conversion to condition

researcharxiv-cs-lg

G0.5: One Autoregressive Stream for Robot Reasoning and Action

arXiv:2608.11739v1 Announce Type: cross Abstract: The prevailing recipe for Vision-Language-Action (VLA) models couples a pretrained VLM with a separately trained flow-matching action expert. This mak

Generative Video Compression Based on Hierarchical Referencing

arXiv:2608.11618v1 Announce Type: new Abstract: Diffusion-based generative video compression has emerged as a promising paradigm to improve perceptual quality, where latent frames are required to be e

researcharxiv-cs-cv

Geometry-aware Incremental Neural Operator for Long-Horizon PDE prediction

arXiv:2608.11237v1 Announce Type: new Abstract: Neural operators have shown strong potential for learning solution operators of partial differential equations (PDEs). However, long-horizon autoregress

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

Gloss-Free Representation Learning for Cross-Dataset Sign Spotting

model-releasesarxiv-cs-cl

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,

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

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?

model-releasesarxiv-cs-cv

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

model-releasesarxiv-cs-lg

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