Search: “benchmark”

Exploring the Effects of Entanglement on Quantum Machine Learning of Pathogen Epitope-Receptor Binding

model-releasesarxiv-cs-lg

arXiv:2606.28655v1 Announce Type: cross Abstract: Parameterized quantum circuits (PQCs) provide a flexible substrate for hybrid quantum machine learning (QML), but their practical value on Noisy Inter

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Research

FADE: Mitigating Hallucinations by Reducing Language-Prior Dominance in Large Vision-Language Models

DGX agent

arXiv:2606.29431v1 Announce Type: new Abstract: Despite the impressive capabilities of Large Vision-Language Models (LVLMs), they remain susceptible to hallucination, generating content inconsistent w

researcharxiv-cs-ai

30 Jun 2026

FAIL: Flow Matching Adversarial Imitation Learning for Image Generation

arXiv:2602.12155v2 Announce Type: replace Abstract: Post-training of flow matching models-aligning the output distribution with a high-quality target-is mathematically equivalent to imitation learning

safetyarxiv-cs-cv

FastPano3D: Feed-Forward Indoor Panoramic 3D Reconstruction from a Single Image

arXiv:2606.30352v1 Announce Type: new Abstract: Recent advances in 3D scene reconstruction have highlighted the intricate trade-offs among rendering quality, inference efficiency, and data dependency.

FD^2: A Dedicated Framework for Fine-Grained Dataset Distillation

arXiv:2603.25144v2 Announce Type: replace-cross Abstract: Dataset distillation (DD) compresses a large training set into a small synthetic set, reducing storage and training cost, and has shown strong

Feature-level Interaction Explanations in Multimodal Transformers

arXiv:2603.13326v2 Announce Type: replace-cross Abstract: Multimodal Transformers often produce predictions without clarifying how different modalities jointly support a decision. Most existing multim

Tools

Featuring Every Eval Ever Results on Hugging Face Model Pages

Hugging Face introduced a feature that displays evaluation results from the 'Every Eval Ever' (EEE) community evaluation initiative directly on model pages, providing users with comprehensive benchmar

toolshugging-face

Hardware

Featuring the man of the moment @dylan522p @shaunmmaguire in today's Training Data episode. Nobody is a more trusted industry insider to the…

Featuring the man of the moment @dylan522p @shaunmmaguire in today's Training Data episode. Nobody is a more trusted industry insider to the biggest infrastructure build-out in history. The story of h

hardwaresonya-huang--x

FedLAS: Feature-Modulated Bidirectional Label Smoothing for Neural Network Calibration

arXiv:2606.28654v1 Announce Type: cross Abstract: Deep Neural Network (DNN) classifiers suffer from poor calibration when their softmax outputs (predictive confidence) deviate from the empirical likel

Few-Shot Domain Incremental Learning via Continual Vision-Language Consolidation

arXiv:2606.30190v1 Announce Type: cross Abstract: Existing domain-incremental learning (DIL) strategies call for massive amounts of data to adapt to new domains and suffer from the overfitting problem

Fisher-Routed Mixture of Experts for Federated Class-Incremental Learning

arXiv:2606.28835v1 Announce Type: cross Abstract: Federated Learning (FL) emerged as a promising distributed machine learning paradigm. However, extending FL to the class incremental learning scenario

Frames2Residual: Spatiotemporal Decoupling for Self-Supervised Video Denoising

arXiv:2603.10417v2 Announce Type: replace Abstract: Self-supervised video denoising methods typically extend image-based frameworks into the temporal dimension, yet they often struggle to integrate in

Applications

FreqOrtho-SR: Frequency-Guided Orthogonal Expert Learning for Real-World Image Super-Resolution

arXiv:2606.28745v1 Announce Type: new Abstract: Diffusion prior-based methods have shown impressive results in real-world image super-resolution (ISR), yet two key challenges persist: balancing pixel-

applicationsarxiv-cs-cv

Friend or Foe

arXiv:2509.00123v2 Announce Type: replace-cross Abstract: A fundamental challenge in microbial ecology is determining whether bacteria compete or cooperate in different environmental conditions. With

researcharxiv-cs-lg

From Local Windows to Adaptive Candidates via Individualized Exploratory: Rethinking Attention for Image Super-Resolution

arXiv:2601.08341v2 Announce Type: replace Abstract: Single Image Super-Resolution (SISR) is a fundamental computer vision task that aims to reconstruct a high-resolution (HR) image from a low-resoluti

From Regulatory Approvals to Patents: Cross-Domain Linking for Cardiovascular Device Traceability

arXiv:2606.28353v1 Announce Type: cross Abstract: Linking FDA-approved medical devices to their underlying United States Patent and Trademark Office (USPTO) patents enables critical applications such

FutureNav: Unified World-Action Modeling for Vision-and-Language Navigation

arXiv:2606.30367v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) in continuous environments requires an agent to ground instructions in egocentric observations while maintaining sp

safetyarxiv-cs-ro

General and Efficient Steering of Diffusion Models

arXiv:2602.11395v2 Announce Type: replace-cross Abstract: Steering diffusion models toward conditions unseen during training typically requires either retraining with conditional inputs or per-step gr

Tutorials

Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding

arXiv:2603.19235v2 Announce Type: replace Abstract: While Multimodal Large Language Models demonstrate impressive semantic capabilities, they often suffer from spatial blindness, struggling with fine-

tutorialsarxiv-cs-cv

GeoEdit: Geometry-Aware Object Editing via Dual-Branch Denoising

arXiv:2606.30003v1 Announce Type: new Abstract: Precisely manipulating objects in a single photograph (translation, rotation, scaling) while obeying 3D physical constraints remains unsolved for diffus

Geometric Algebra Meets Cartesian Tensors: Higher-Order Equivariance for Interatomic Potentials

arXiv:2606.29584v1 Announce Type: cross Abstract: Cl(3,0) interatomic potentials, despite their algebraic elegance, predict force magnitudes accurately but force directions poorly. Across ten rMD17 mo

researcharxiv-cs-lg

Golden Hour Divide: Trauma Care Accessibility and Resource Vulnerability in Sri Lanka

arXiv:2606.29889v1 Announce Type: new Abstract: Timely intensive care dictates survival, yet emergency infrastructure remains unevenly distributed across Sri Lanka. While pre-hospital services have ex

safetyarxiv-cs-lg

Graph-GSReg: Leveraging 3D Scene Graphs for Gaussian Splatting Registration

arXiv:2606.29782v1 Announce Type: new Abstract: Merging multiple 3D Gaussian Splatting (3DGS) scenes into a single unified Gaussian representation is essential for large-scale 3D mapping and long-term

Grounding Sim-to-Real Generalization in Robotic Manipulation: An Empirical Study with Vision-Language-Action Models

arXiv:2603.22876v2 Announce Type: replace-cross Abstract: Learning a generalist control policy for robotic manipulation typically relies on large-scale datasets. Given the high cost of real-world data

Hard-constraint physics-residual networks for hydrogen crossover prediction and high-pressure extrapolation in PEM water electrolysis

arXiv:2511.05879v5 Announce Type: replace-cross Abstract: Hydrogen crossover is a critical safety and efficiency constraint in high-pressure polymer electrolyte membrane water electrolysis (PEMWE), bu

Hardware

HARD-KV: Head-Adaptive Regularization for Decoding-time KV Compression

arXiv:2606.28831v1 Announce Type: cross Abstract: Long-context LLM inference faces a fundamental conflict: head-adaptive compression algorithms (e.g., Top-p nucleus sampling) offer superior accuracy b

hardwarearxiv-cs-ai

HERO: Improving the Reliability and Sensitivity of Generative Model Evaluation Using Historical Data

arXiv:2606.29784v1 Announce Type: cross Abstract: Reliable generative AI models critically rely on expert human annotations to evaluate output quality, yet these 'gold' labels are expensive to collect

Hierarchical Experimentalist Agents

arXiv:2606.29315v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to take actions in the real world and support human decision-making, yet most agents rely on parametr

High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative Despeckling

arXiv:2606.30511v1 Announce Type: new Abstract: Reliable high-resolution flood extent mapping from satellite imagery remains constrained by limited data fidelity and sensor-specific artifacts. Multisp

HippoSpark: An On-Demand Experience System for LLM Reasoning

arXiv:2606.29929v1 Announce Type: new Abstract: Distilling historical trajectories into reusable experience to enhance future problem-solving has become a focal point of recent LLM research. However,

Agents

HMARS: A Hierarchical Multi-Agent Memory System for Long-Context Reasoning

arXiv:2606.28349v1 Announce Type: cross Abstract: Long-context reasoning requires models to access, retrieve, and integrate evidence scattered across documents, dialogues, and accumulated interaction

agentsarxiv-cs-ai

How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation

arXiv:2606.28358v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) aims to enhance the trustworthiness of Large Language Models (LLMs) by grounding their outputs in external docume

How Far Do On-Prem Open LLMs Get on Text-to-SQL? A Cross-Family Size x Technique Frontier on BIRD

model-releasesarxiv-cs-cl

arXiv:2606.29733v1 Announce Type: new Abstract: Organizations that cannot send data to a cloud API increasingly ask: how good is Text-to-SQL if the model must run on-premises on open weights, and whic

How to Train Your Long-Context Visual Document Model

arXiv:2602.15257v3 Announce Type: replace-cross Abstract: We present the first comprehensive, large-scale study of training long-context vision language models up to 344K context, targeting long-docum

HyBIRD: Hyperbolic Bridge Retrieval and Diagnosis for Methodology Inspiration Retrieval

arXiv:2606.28336v1 Announce Type: cross Abstract: Methodology Inspiration Retrieval (MIR) asks a system to retrieve prior papers whose methods can inspire a new research proposal. Unlike general scien

Improved Predictive Performance and Interpretability for Mesomorphic Neural Networks Using Local Fidelity Regularization

model-releasesarxiv-cs-lg

arXiv:2606.29951v1 Announce Type: new Abstract: Interpretable Mesomorphic Neural Networks (IMNs) offer a promising framework that combines the predictive power of deep neural networks with the interpr

Improving Coherence in Hierarchical Time Series Forecasting using Structured Temporal Fusion

model-releasesarxiv-cs-lg

arXiv:2606.28553v1 Announce Type: new Abstract: In many real-world applications, such as retail sales, energy usage, and supply chain planning, forecasting is performed across hierarchical structures.

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver

arXiv:2405.01906v3 Announce Type: replace Abstract: In modern intelligent transportation systems (ITS), particularly in freight transportation and logistics, real-time route planning is crucial. It pr

InterEdit: Navigating Text-Guided 3D Dyadic Human Motion Editing

arXiv:2603.13082v2 Announce Type: replace Abstract: Text-guided 3D motion editing has seen success in single-person scenarios, but its extension to multi-person settings is less explored due to limite

Invariant Reasoning Directions in Latent Trajectories of Language Models

arXiv:2606.29164v1 Announce Type: cross Abstract: Latent reasoning models perform multi-step inference directly in hidden-state space, yet the structure of these latent reasoning trajectories remains

ITSPACE: Monotone Gaussian Optimal Transport Updates

arXiv:2606.30523v1 Announce Type: new Abstract: Covariance matrices serve as compact descriptors of feature distributions in many machine-learning pipelines, including domain adaptation and Gaussian e

safetyarxiv-cs-lg

Agents

KbSD: Knowledge Boundary aware Self-Distillation for Behavioral Calibration in Agentic Search

arXiv:2606.29863v1 Announce Type: new Abstract: Agentic search equips large language models with dynamic retrieval abilities, but existing reinforcement learning methods remain limited by reward spars

agentsarxiv-cs-cl

Local Ai

KernelSight-LM: A Kernel-Level LLM Inference Simulator

arXiv:2606.28565v1 Announce Type: cross Abstract: As large language models (LLMs) move into production serving, practitioners must rapidly evaluate inference performance across diverse hardware, model

local-aiarxiv-cs-ai

Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement

arXiv:2601.21864v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit social biases that reinforce harmful stereotypes, limiting their safe deployment. Most existing debiasing metho

LatentRevise: Learning from Zero-Hit Reasoning

arXiv:2606.29938v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is bottlenecked by hard prompts on which correct trajectories have low probability, so sampling mi

safetyarxiv-cs-cl

LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion

arXiv:2603.14526v2 Announce Type: replace Abstract: The recent success of inference-time scaling in large language models has inspired similar explorations in video diffusion. In particular, motivated

Learning Cross-view Correspondences for Geo-localization on Planetary Surfaces

arXiv:2606.29821v1 Announce Type: new Abstract: Maintaining global position awareness is a fundamental challenge for planetary surface exploration, since satellite-based positioning systems are unavai

Learning Efficient 4D Gaussian Representations from Monocular Videos with Flow Splatting

arXiv:2606.29976v1 Announce Type: new Abstract: Reconstructing dynamic 3D scenes from monocular videos is challenging due to scene complexity and temporal dynamics. With the advancement of 3D Gaussian