Search: “models”

Explainable AI Through a Democratic Lens: DhondtXAI for D'Hondt-Projected Feature Attribution

arXiv:2411.05196v3 Announce Type: replace Abstract: This study presents DhondtXAI as a SHAP-independent, D'Hondt-based attribution framework for tabular XAI. Instead of model-native feature importance

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Model Releases

Explainable Forensics of Manipulated Segments in Untrimmed Long Videos

DGX agent

arXiv:2606.02402v1 Announce Type: new Abstract: The rapid advancement of AI-driven video generation has transformed content creation, while simultaneously increasing the risk of misinformation through

model-releasesarxiv-cs-cv

2 Jun 2026

ExpWeaver: LLM Agents Learn from Experience via Latent RAG

model-releasesarxiv-cs-cl

arXiv:2606.01041v1 Announce Type: new Abstract: Experience learning has achieved promising results in enhancing LLM agent planning and reasoning by integrating past interactions as reusable knowledge.

Extending Causal Metamodeling to a non-Markovian Queue

arXiv:2606.00795v1 Announce Type: cross Abstract: Metamodels for discrete-event simulations approximate the behavior of simulation models without running expensive simulations. Prior work introduced m

FALAT: Tracing Failures in LLM Agent Trajectories via Dependency-Guided Search

arXiv:2606.00765v1 Announce Type: new Abstract: LLM-based agents increasingly solve complex tasks through long trajectories involving reasoning steps, tool calls, and inter-agent communication. Howeve

Fast-SAM3D: 3Dfy Anything in Images but Faster

model-releasesarxiv-cs-cv

arXiv:2602.05293v2 Announce Type: replace Abstract: SAM3D enables scalable, open-world 3D reconstruction from complex scenes, yet its deployment is hindered by prohibitive inference latency. In this w

FedCF: Fair Federated Conformal Prediction

arXiv:2509.22907v2 Announce Type: replace Abstract: Conformal Prediction (CP) is a widely used technique for quantifying uncertainty in machine learning models. In its standard form, CP offers probabi

safetyarxiv-cs-lg

Finer Parameter Steps for Low-Rank PEFT: A Controlled Study with CP Tensor Adapters

arXiv:2606.00428v1 Announce Type: cross Abstract: Low-rank adapters are usually compared by sweeping a small set of ranks, but the rank also fixes the resolution of the parameter budget. For a 2048{im

Flexible Control of 3D CT Generation via Text and Semantically-Defined Segmentation Prompts

arXiv:2606.00967v1 Announce Type: new Abstract: Generative models for volumetric medical images have found many applications in medical imaging, ranging from data augmentation to serving as priors for

safetyarxiv-cs-cv

Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics

arXiv:2602.24201v2 Announce Type: replace Abstract: Estimating density ratios between pairs of intractable data distributions is a core problem in probabilistic modeling, enabling principled compariso

researcharxiv-cs-lg

FlowNar: Scalable Streaming Narration for Long-Form Videos

arXiv:2606.00620v1 Announce Type: new Abstract: Recent Large Multimodal Models (LMMs), primarily designed for offline settings, are ill-suited for the dynamic requirements of streaming video. While re

Food Noise & False Safety: A Systematic Evaluation of How LLMs Fail to Adapt to Eating Disorder Queries with Clinician Feedback

arXiv:2606.02444v1 Announce Type: new Abstract: Recent evidence shows that people with eating disorders (EDs) are increasingly seeking guidance, advice, and emotional support from Large Language Model

ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment

arXiv:2606.00644v1 Announce Type: new Abstract: AI research often requires decisions before future evidence exists: which bottleneck to attack, which direction to pursue, or where a project should be

ForestMamba: Sparse Mamba with Geometry-guided Queries for 3D Forest Point Cloud Segmentation

arXiv:2606.01549v1 Announce Type: new Abstract: AI-based semantic and instance segmentation of terrestrial and drone LiDAR point clouds is emerging as a transformative approach for converting the comp

local-aiarxiv-cs-cv

Foundation-Preserving Adaptation via Generalized Rayleigh-Quotient Optimization

arXiv:2606.00132v1 Announce Type: cross Abstract: While finetuning effectively adapts foundation models to specialized downstream tasks, it can degrade nontarget capabilities acquired during pretraini

From Features to Actions: Explainability in Traditional and Agentic AI Systems

arXiv:2602.06841v4 Announce Type: replace Abstract: Over the last decade, Explainable AI has primarily focused on interpreting individual model predictions, producing post-hoc explanations that relate

Applications

FW-NKF: Frequency-Weighted Neural Kalman Filters

arXiv:2606.02251v1 Announce Type: cross Abstract: Robust state estimation is central to robotic autonomy, yet classical Kalman filters struggle with frequency-dependent disturbances and model mismatch

applicationsarxiv-cs-ai

Generate in Reconstruction Space, Match in Semantic Space: Transport Geometry for One-Step Generation

arXiv:2606.00514v1 Announce Type: cross Abstract: Generative modeling and self-supervised representation learning (SSL) optimize structurally different objectives: generative training rewards distribu

GenPT: Beyond Self-Report for Reliable LLM Psychometrics via Generative Projective Testing

arXiv:2606.00860v1 Announce Type: cross Abstract: Self-report questionnaires remain the prevailing tool for probing the psychological states of persona-conditioned agents (PC-Agents). However, classic

GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks

arXiv:2506.16114v3 Announce Type: replace-cross Abstract: Generative recommendations (GR), which usually include item tokenizers and generative Large Language Models (LLMs), have demonstrated remarkab

Agents

Goal2Pixel: Grounding Goals to Pixels for Vision-Language Navigation

arXiv:2606.01621v1 Announce Type: new Abstract: Vision-language models (VLMs) have become a common foundation for vision-and-language navigation in continuous environments (VLN-CE). Yet most VLM-based

agentsarxiv-cs-cv

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation

arXiv:2606.01412v1 Announce Type: new Abstract: Post-training quantization is widely used for compressing large neural networks, but aggressive low-bit quantization can significantly degrade model qua

researcharxiv-cs-lg

GRANITE : a Byzantine-Resilient Dynamic Gossip Learning Framework

arXiv:2504.17471v2 Announce Type: replace-cross Abstract: Gossip Learning (GL) is a decentralized learning paradigm where users iteratively exchange and aggregate models with a small set of neighborin

HAIM: Human-AI Music Datasets for AI Music Production Tracking Benchmark

arXiv:2606.01686v1 Announce Type: cross Abstract: As generative platforms such as Suno and Udio reach human-grade audio quality, the scope of AI's utility has expanded across the entire music producti

HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization

arXiv:2603.03741v2 Announce Type: replace-cross Abstract: To improve generalization and resilience in human-robot collaboration (HRC), robots must contend with diverse combinations of human behaviors

Harness-1: Reinforcement Learning for Search Agents with State-Externalizing Harnesses

arXiv:2606.02373v1 Announce Type: new Abstract: Search agents are often trained as policies over growing transcripts: the model must decide how to search while also remembering what it has seen, which

Hist2Style: Histogram-Guided Stylization with Bilateral Grids

arXiv:2606.01819v1 Announce Type: new Abstract: Photorealistic style transfer aims to match the color and tone of an input image to that of a style target while preserving the content and details of t

local-aiarxiv-cs-cv

HiTokSR: A Coarse-to-Fine Tokenizer with Hierarchical Codebooks for High-Fidelity Real-World Image Super-Resolution

arXiv:2606.01157v1 Announce Type: new Abstract: Vector-quantized (VQ) generative models have shown promising results in real-world image super-resolution (Real-ISR). However, existing methods typicall

safetyarxiv-cs-cv

HLL: Can Agents Cross Humanity's Last Line of Verification?

arXiv:2606.02449v1 Announce Type: new Abstract: Multimodal agents are increasingly expected to operate interfaces on behalf of users, raising a central deployment question: can they truly substitute f

HMPO: Hybrid Median-length Policy Optimization for Chain-of-Thought Compression

arXiv:2606.01934v1 Announce Type: cross Abstract: Large language models achieve remarkable performance via extended chain-of-thought (CoT) reasoning, yet this lengthy process incurs substantial infere

safetyarxiv-cs-cl

HOLA: Holistic Multi-Modal Alignment for Open-Set 3D Recognition

arXiv:2606.01334v1 Announce Type: new Abstract: Open-set 3D recognition requires models that generalize to rare or unseen categories. Recent approaches address this by distilling language-vision knowl

safetyarxiv-cs-cv

How Hard Can It Be? Hardness-Aware Multi-Objective Unlearning

arXiv:2606.02119v1 Announce Type: cross Abstract: Machine unlearning aims to remove the influence of specific forget training data due to privacy, copyright or bias concerns while maintaining the mode

How Optimality Structures Sparse Dictionaries: A Theory for Understanding SAE Representations

arXiv:2606.02385v1 Announce Type: cross Abstract: Sparse Autoencoders (SAEs) have found success parsing neural representations into interpretable concepts, providing a basis for understanding and cont

local-aiarxiv-cs-lg

HR-VILAGE-3K3M: A Human Respiratory Viral Immunization Longitudinal Gene Expression Dataset for Systems Immunity

model-releasesarxiv-cs-lg

arXiv:2505.14725v2 Announce Type: replace-cross Abstract: Respiratory viral infections pose a global health burden, yet the cellular immune mechanisms underlying protection and pathology remain unclea

HRTFformer: A Spatially-Aware Transformer for Individual HRTF Upsampling in Immersive Audio Rendering

arXiv:2510.01891v2 Announce Type: replace-cross Abstract: Individual Head-Related Transfer Functions (HRTFs) are starting to be introduced in many commercial immersive audio applications and are cruci

Implicit Regularization for Multi-label Feature Selection

arXiv:2411.11436v2 Announce Type: replace-cross Abstract: In this paper, we address the problem of feature selection in the context of multi-label learning, by using a new estimator based on implicit

Improving Combined Detection and Classification of TEM Defects via Mask-Conditioned Latent Diffusion Augmentation

arXiv:2606.02532v1 Announce Type: new Abstract: Analyzing microstructural defects in transmission electron microscopy (TEM) images, particularly in irradiated metal alloys, is often limited by the ava

Initialization is Half the Battle: Generating Diverse Images from a Guidance Potential Posterior

arXiv:2606.02453v1 Announce Type: cross Abstract: Despite the remarkable fidelity of generative models, they frequently suffer from mode collapse. Existing strategies for enhancing diversity predomina

Interpretable Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification using Multi-Omics Data

arXiv:2503.22939v4 Announce Type: replace Abstract: The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational mod

researcharxiv-cs-lg

Applications

KDH-CAD: Knowledge-data hybrid CAD learning under data scarcity

arXiv:2606.01702v1 Announce Type: cross Abstract: Deep learning in computer-aided design (CAD) remains fundamentally constrained by the data scarcity challenge: authentic CAD data is difficult to coll

applicationsarxiv-cs-lg

Applications

KG-Guard: Graph-Based Hallucination Detection for Knowledge Base Question Answering

arXiv:2606.00328v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for knowledge base question answering (KBQA), where answering requires selecting entities from a ques

applicationsarxiv-cs-lg

KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices

model-releasesarxiv-cs-cl

arXiv:2601.21579v2 Announce Type: replace Abstract: The success of Hyper-Connections (HC) in neural networks (NN) has also highlighted issues related to training instability and restricted scalability

Learning Implicit Bias in Generative Spaces for Accelerating Protein Dynamics Emulation

arXiv:2606.01833v1 Announce Type: cross Abstract: Generative emulators of protein dynamics produce plausible trajectories at a fraction of the cost of molecular dynamics, but they inherit their traini

Learning Multi-Modal Trajectory Policies for Data-Efficient Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.01047v1 Announce Type: new Abstract: Robotic manipulation requires the effective integration of heterogeneous inputs, including visual observations, language instructions, and trajectory re

Agents

Learning-To-Measure: In-Context Active Feature Acquisition

arXiv:2510.12624v2 Announce Type: replace-cross Abstract: Active feature acquisition (AFA) is a sequential decision-making problem where the goal is to improve model performance for test instances by

agentsarxiv-cs-ai

Learning to Trim: End-to-End Causal Graph Pruning with Dynamic Anatomical Feature Banks for Medical VQA

arXiv:2603.26028v2 Announce Type: replace Abstract: Medical Visual Question Answering (MedVQA) models often exhibit limited generalization due to reliance on dataset-specific correlations, such as rec

LLM-Driven Co-Evolutionary Automated Heuristic Design for Bi-Component Coupled Combinatorial Optimization

arXiv:2606.00718v1 Announce Type: new Abstract: While Large Language Models (LLMs) have recently shown promise in Automated Heuristic Design (AHD), existing methods typically generate and evolve heuri

Local Preferential Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2606.02351v1 Announce Type: new Abstract: Bayesian optimization (BO) is a popular and effective approach for tuning expensive, noisy experiments, but requires the formulation of an explicit obje