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Code-on-Graph: Iterative Programmatic Reasoning via Large Language Models on Knowledge Graphs

arXiv:2606.03705v1 Announce Type: new Abstract: Knowledge Graphs (KGs) are widely used to mitigate the limitations of Large Language Models (LLMs), such as outdated knowledge and hallucinations. Exist

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Conditional Latent Diffusion Model with Fourier-based Motion Modelling for Virtual Population Synthesis

DGX agent

arXiv:2606.03827v1 Announce Type: cross Abstract: In-silico trials of medical devices require the generation of virtual populations of anatomies. In cardiovascular applications, virtual anatomy is typ

researcharxiv-cs-ai

3 Jun 2026

Conformal Language Modeling via Posterior Sampling

arXiv:2606.03731v1 Announce Type: new Abstract: Large Language Models remain plagued by hallucinations. Recent work has sought to tame their prevalence using statistical techniques based on conformal

CORE: Conflict-Oriented Reasoning for General Multimodal Manipulation Detection

arXiv:2606.03066v1 Announce Type: new Abstract: The rapid rise of generative AI has made multimodal fake news increasingly realistic and pervasive, posing severe threats to public trust and social sta

CoughSense: Five-Class Respiratory Disease Classification via Whisper Encoder Fine-Tuning and Dual-Encoder Cross-Attention Fusion with Balanced Contrastive Learning

arXiv:2606.02998v1 Announce Type: new Abstract: Automated cough analysis offers a path to low-cost respiratory screening, but most existing work stops at binary COVID-19 detection. A practical tool ne

CropCraft: A Procedural World Generator for Robotic Simulation of Agricultural Tasks

arXiv:2511.02417v2 Announce Type: replace Abstract: The adoption of agroecological practices in modern agriculture requires robotic systems capable of operating in highly diverse and complex field env

Cross-Modal Contrastive Learning of ECG and Angiography Representations for Severe Stenosis Classification

arXiv:2606.02605v1 Announce Type: cross Abstract: Coronary artery stenosis is a common cardiovascular disease, with severe, untreated cases posing significant risks of heart attack. Although coronary

CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction

arXiv:2508.03668v2 Announce Type: replace Abstract: Click-Through Rate (CTR) prediction, a core task in recommendation systems, estimates user click likelihood using historical behavioral data. Modeli

researcharxiv-cs-cl

Decomposing how prompting steers behavior

arXiv:2606.03093v1 Announce Type: new Abstract: Prompting steers large language models (LLMs) and vision-language models (VLMs) without weight updates, but it remains unclear how instruction changes r

DeMuon: A Decentralized Muon for Matrix Optimization over Graphs

arXiv:2510.01377v2 Announce Type: replace-cross Abstract: In this paper, we propose DeMuon, a method for decentralized matrix optimization over a given communication topology. DeMuon incorporates matr

Depth from Dual Differential Defocus and Stereo Consensus

arXiv:2606.02906v1 Announce Type: cross Abstract: We introduce D^3S Consensus, a physics-based, closed-form algorithm that unifies depth-from-defocus (DfD) and stereo to achieve highly accurate depth

DiffUNet^2: Bidirectional Prediction, Probabilistic Generation and Collaborative Visual Discovery for Scientific Data

arXiv:2606.03926v1 Announce Type: cross Abstract: Modeling temporal evolution is important to analyzing and reasoning about scientific phenomena, yet most machine learning methods provide deterministi

Diffusing in the Right Space: A Systematic Study of Latent Diffusability

arXiv:2606.03578v1 Announce Type: new Abstract: Latent diffusion models leverage visual tokenizers to compress images into latent spaces for efficient generative modeling. However, better reconstructi

Direct Informed Sampling on Riemannian Manifolds via Loewner Order Lower Bounds

arXiv:2606.02879v1 Announce Type: new Abstract: Informed sampling techniques accelerate sampling-based motion planners by focusing the search on promising regions of the state space, yet most existing

researcharxiv-cs-ro

Distribution-Calibrated Inference Time Compute for Thinking LLM-as-a-Judge

arXiv:2512.03019v2 Announce Type: replace-cross Abstract: Thinking Large Language Models (LLMs) used as judges for pairwise preferences remain noisy at the single-sample level, and common aggregation

dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching

arXiv:2506.06295v2 Announce Type: replace-cross Abstract: Autoregressive Models (ARMs) have long dominated the landscape of Large Language Models. Recently, a new paradigm has emerged in the form of d

Don't Gamble, GAMBLe: An Analytical Framework for AI-Driven Research Systems

arXiv:2606.02863v1 Announce Type: new Abstract: AI-Driven Research Systems (ADRS) -- systems coupling LLMs with automated evaluation to discover algorithms, proofs, and designs -- are being optimized

DRAN: A Distribution and Relation Adaptive Network for Spatio-temporal Forecasting

arXiv:2504.01531v4 Announce Type: replace Abstract: Accurate predictions of spatio-temporal systems are crucial for tasks such as system management, control, and crisis prevention. However, the inhere

dstack-capsule: Pod-Level Remote Attestation for Confidential Workloads on Kubernetes

arXiv:2606.03323v1 Announce Type: cross Abstract: The rise of LLM-as-a-Service and other confidential cloud workloads demands cryptographic proof that user data is processed in a trusted, untampered e

DTKG: Dual-Track Knowledge Graph-Verified Reasoning Framework for Multi-Hop QA

arXiv:2510.16302v2 Announce Type: replace Abstract: Multi-hop reasoning for question answering (QA) plays a critical role in retrieval-augmented generation (RAG) for modern large language models (LLMs

DXA-Derived Skeletal Phenotypes and Hip Fracture Risk: A Backdoor-Adjusted Causal Analysis

arXiv:2606.02625v1 Announce Type: cross Abstract: Purpose: To compare dual-energy X-ray absorptiometry (DXA)-derived hip skeletal phenotypes in relation to hip fracture risk using prespecified confoun

Dynamic Objective Selection with Safeguards and LLM Oversight for Financial Decision-Making

arXiv:2606.03704v1 Announce Type: new Abstract: Financial decision-making tasks such as stock recommendation and portfolio allocation typically estimate future return and risk and then select trades o

Echo-POSED: Geometric Self-Distillation for Echocardiography Guidance

arXiv:2606.02634v1 Announce Type: cross Abstract: We introduce Echo-POSED, a self-supervised framework for real-time transthoracic echocardiography (TTE) guidance that recommends probe adjustments dir

Efficient Hyperparameter Optimization for LLM Reinforcement Learning

arXiv:2606.03073v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is highly sensitive to hyperparameter configurations, making hyperparameter optimization

Efficient Transformer-Based Localized Patch Sampling for Choroid Plexus Segmentation in Multiple Sclerosis

arXiv:2606.03566v1 Announce Type: cross Abstract: Background: The lateral ventricle choroid plexus (LVCP) is gaining recognition as a key imaging biomarker for multiple sclerosis (MS) related to physi

Electromagnetic Navigation for Femoral Osteotomy Using High-Accuracy X-ray-to-CT Registration

arXiv:2606.03893v1 Announce Type: new Abstract: Accurate execution of preoperative plans in corrective femoral osteotomies remains challenging. Current techniques are limited by variable accuracy, inv

Enhancing Paraphrase Type Generation: The Impact of DPO and RLHF Evaluated with Human-Ranked Data

arXiv:2506.02018v2 Announce Type: replace Abstract: Paraphrasing re-expresses meaning to enhance applications like text simplification, machine translation, and question-answering. Specific paraphrase

researcharxiv-cs-cl

Enhancing Protein-Protein Interaction Prediction with Hierarchical Motif-based Multimodal Protein Embedding

arXiv:2606.02629v1 Announce Type: cross Abstract: Protein-protein interactions (PPIs) are essential for many biological processes. However, existing PPI prediction approaches suffer from two major lim

EntangleCodec: A Unified Discrete Audio Tokenizer via Semantic-Acoustic Entanglement

arXiv:2606.02739v1 Announce Type: cross Abstract: Audio tokenizers serve as the discrete interface between continuous audio and Audio Language Models (ALMs), but existing tokenizers often struggle to

EqGINO: Equivariant Geometry-Informed Fourier Neural Operators for 3D PDEs

arXiv:2606.03260v1 Announce Type: cross Abstract: Deep learning surrogates for 3D Partial Differential Equations (PDEs) often fail to generalize across geometric transformations because they depend he

Estimating Central, Peripheral, and Temporal Visual Contributions to Human Decision Making in Atari Games

arXiv:2604.04439v2 Announce Type: replace-cross Abstract: We study how different visual information sources contribute to human decision making in dynamic visual environments. Using Atari-HEAD, a larg

Exact equivariance, kept through training, buys zero-shot generalisation across the symmetry group

arXiv:2606.03003v1 Announce Type: cross Abstract: A latent world model built from an equivariant encoder E and an equivariant predictor f inherits a provable symmetry of its training loss: when the wo

Exploiting Verification-Generation Gap: Test-Time Reinforcement Learning with Confidence-Conditioned Verification

arXiv:2606.03608v1 Announce Type: cross Abstract: Test-time reinforcement learning has emerged as a promising paradigm for enhancing the complex reasoning abilities of large language models in a compl

Exploring Easy Boosts for Lidar Semantic Scene Completion

arXiv:2606.03992v1 Announce Type: new Abstract: This paper investigates 'free lunch' strategies to boost the performance of lidar semantic scene completion (SSC) without requiring complex architectura

Fast and Expressive Multi-Byte Prediction with Probabilistic Circuits

arXiv:2511.11346v2 Announce Type: replace Abstract: Multi-token prediction (MTP) is a prominent strategy to significantly speed up generation in large language models (LLMs), especially in byte-level

Fast-dLLM++: Frechet Profile Decoding for Faster Diffusion LLM Inference

arXiv:2606.02955v1 Announce Type: cross Abstract: Diffusion large language models promise parallel token generation, yet inference remains bottlenecked by deciding which masked tokens can be safely co

Fast Unlearning at Scale via Margin Self-Correction

arXiv:2606.02920v1 Announce Type: new Abstract: Language-model unlearning updates a trained model to behave as if it had not seen selected training examples, while preserving utility and avoiding cost

Finding Needles in the Haystack: Transductive Active Labeling in Ecology

arXiv:2606.03821v1 Announce Type: new Abstract: Active learning is now standard practice in labeling ecological data, enabling ecologists to quickly process large volumes of field data to understand a

Fixed-Time Dynamic Landing of Quadrotors using Adaptive Unscented Kalman Filtering and Nonlinear Model Predictive Control

arXiv:2606.02658v1 Announce Type: new Abstract: This paper introduces an estimation and control framework for dynamic landing of multi-rotor uncrewed aerial vehicles on moving platforms. The proposed

researcharxiv-cs-ro

FlashbackCL: Mitigating Temporal Forgetting in Federated Learning

arXiv:2606.03939v1 Announce Type: cross Abstract: Federated Learning (FL) of foundation and edge models increasingly targets deployments where client data distributions drift over time, yet existing f

Flicker-DDPM: Accelerating Denoising Diffusion via 1/f Colored Noise Injection

arXiv:2606.03393v1 Announce Type: new Abstract: We propose a novel diffusion model, Flicker-DDPM, which incorporates flicker (1/f) noise inspired by self-organized criticality (SOC), a widely observed

FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences

arXiv:2606.03330v1 Announce Type: cross Abstract: Literature reveals that a Large Language Model's (LLM) behavior is not only conditioned by its original weights but also its instance-level parameters

FlowGuard: Flow Matching for Identity-Independent Detection of Data-Free Model Stealing Attacks on Energy System Intrusion Detection Systems

arXiv:2606.03430v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-based Intrusion Detection Systems (IDS) deployed in energy infrastructure are vulnerable to model theft attacks, which al

From Non-Convex to Strongly Convex: Curvature-Adaptive FTPL for Online Optimization

arXiv:2606.02948v1 Announce Type: new Abstract: Curvature adaptivity is a classical theme in online optimization: for convex Lipschitz losses, adaptive methods interpolate between the optimal O(sqrt{T

From None to All: Self-Supervised 3D Reconstruction via Novel View Synthesis

arXiv:2603.27455v2 Announce Type: replace Abstract: In this paper, we introduce NAS3R, a self-supervised feed-forward framework that jointly learns explicit 3D geometry and camera parameters with no g

FSA-GRPO: Teaching Auditory LLMs to Use Few-shot Demonstrations

arXiv:2606.02615v1 Announce Type: cross Abstract: Few-shot prompting provides an effective way to adapt auditory large language models to low-resource tasks such as children's speech recognition. Howe

GARDEN: Gravity-Aligned Reconstruction of Disentangled ENvironments from RGB images

arXiv:2606.03921v1 Announce Type: new Abstract: Converting multi-view RGB observations into simulation-ready 3D environments remains challenging because current reconstruction pipelines produce monoli

Geometric Adaptive Control for a Quadrotor UAV with Wind Disturbance Rejection

arXiv:1803.06363v2 Announce Type: cross Abstract: This paper presents a geometric adaptive control scheme for a quadrotor unmanned aerial vehicle, where the effects of unknown, unstructured disturbanc

researcharxiv-cs-ro