Search: “research”

Do LLMs have core beliefs?

arXiv:2605.03255v1 Announce Type: new Abstract: The rise of Large Language Models (LLMs) has sparked debate about whether these systems exhibit human-level cognition. In this debate, little attention

Do Not Waste Your Rollouts: Recycling Search Experience for Efficient Test-Time Scaling

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arXiv:2601.21684v2 Announce Type: replace Abstract: Test-Time Scaling enhances the reasoning capabilities of Large Language Models by allocating additional inference compute to broaden the exploration

researcharxiv-cs-cl

6 May 2026

Double Rectified Linear Unit-based Modular Semantics for Quantitative Bipolar Argumentation Framework

arXiv:2605.02551v1 Announce Type: new Abstract: Quantitative Bipolar Argumentation Frameworks (QBAFs) provide an alternative approach to computing argument acceptability in Bipolar Argumentation Frame

Dynamic Distillation and Gradient Consistency for Robust Long-Tailed Incremental Learning

arXiv:2605.03364v1 Announce Type: new Abstract: The task of Long-tailed Class Incremental Learning (LT-CIL) addresses the sequential learning of new classes from datasets with imbalanced class distrib

E-MIA: Exam-Style Black-Box Membership Inference Attacks against RAG Systems

arXiv:2605.00955v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) equips large language models (LLMs) with external evidence by retrieving documents at inference time, but it also

Ecologically-Constrained Task Arithmetic for Multi-Taxa Bioacoustic Classifiers Without Shared Data

arXiv:2605.03914v1 Announce Type: cross Abstract: Training data for bioacoustics is scattered across taxa, regions, and institutions. Centralizing it all is often infeasible. We show that independentl

Effect-Transparent Governance for AI Workflow Architectures: Semantic Preservation, Expressive Minimality, and Decidability Boundaries

arXiv:2605.01030v2 Announce Type: new Abstract: We present a machine-checked formalization of structurally governed AI workflow architectures and prove that effect-level governance can be imposed with

EFGPP: Exploratory framework for genotype-phenotype prediction

arXiv:2605.02954v1 Announce Type: cross Abstract: Predicting complex human traits from genetic data is challenging because different genetic, clinical, and molecular data sources often contain differe

EMOVIS: Emotion-Optimized Image Processing

arXiv:2605.03131v1 Announce Type: cross Abstract: In cinematography, visual attributes such as color grading, contrast, and brightness are manipulated to reinforce the emotional narrative of a scene.

Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response

arXiv:2510.12061v2 Announce Type: replace Abstract: Effective disaster response is essential for safeguarding lives and property. Existing statistical approaches often lack semantic context, generaliz

Enhancing AI-Based ECG Delineation with Deep Learning Denoising Techniques

arXiv:2605.03183v1 Announce Type: new Abstract: Evaluating canine electrocardiograms (ECGs) is challenging due to noise that can obscure clinically relevant cardiac electrical activity. Common sources

Tutorials

Enhancing Visual Question Answering with Multimodal LLMs via Chain-of-Question Guided Retrieval-Augmented Generation

arXiv:2605.03790v1 Announce Type: new Abstract: With advances in multimodal research and deep learning, Multimodal Large Language Models (MLLMs) have emerged as a powerful paradigm for a wide range of

tutorialsarxiv-cs-cv

Entanglement is Half the Story: Post-Selection vs. Partial Traces

arXiv:2605.02385v1 Announce Type: cross Abstract: While tensor networks have their traditional application in simulating quantum systems, in the recent decade they have gathered interest as machine le

Epistemic Reject Option Prediction

arXiv:2511.04855v2 Announce Type: replace Abstract: In high-stakes applications, predictive models must not only produce accurate predictions but also quantify and communicate their uncertainty. Rejec

Evaluating Generative Models as Interactive Emergent Representations of Human-Like Collaborative Behavior

arXiv:2605.03855v1 Announce Type: new Abstract: Human-AI collaboration requires AI agents to understand human behavior for effective coordination. While advances in foundation models show promising ca

researcharxiv-cs-ro

Evaluating Reasoning Models for Queries with Presuppositions

arXiv:2605.03050v1 Announce Type: new Abstract: Millions of users turn to AI models for their information needs. It is conceivable that a large number of user queries contain assumptions that may be f

Exact and Approximate Algorithms for Polytree Learning

arXiv:2605.03622v1 Announce Type: cross Abstract: Polytrees are a subclass of Bayesian networks that seek to capture the conditional dependencies between a set of n variables as a directed forest and

Exact ReLU realization of tensor-product refinement iterates

arXiv:2605.03917v1 Announce Type: cross Abstract: We study scalar dyadic refinement operators on R^2 of the form (Vf)(x,y) = sum_{(j,k) in Z^2} c_{j,k} f(2x-j, 2y-k), where only finitely many mask coe

ExaGPT: Example-Based Machine-Generated Text Detection for Human Interpretability

arXiv:2502.11336v2 Announce Type: replace Abstract: Detecting texts generated by Large Language Models (LLMs) could cause grave mistakes due to incorrect decisions, such as undermining students' acade

Exploring Pass-Rate Reward in Reinforcement Learning for Code Generation

arXiv:2605.02944v1 Announce Type: new Abstract: Reinforcement learning (RL) from unit-test feedback has become a standard post-training recipe for improving large language models (LLMs) on code genera

Feasibility-aware Hybrid Control for Motion Planning under Signal Temporal Logics

arXiv:2605.03662v1 Announce Type: new Abstract: In this work, a novel method for planar task and motion planning based on hybrid modeling is proposed. By virtue of a discrete variable which models loc

researcharxiv-cs-ro

Finite-Size Gradient Transport in Large Language Model Pretraining: From Cascade Size to Intensive Transport Efficiency

arXiv:2605.02968v1 Announce Type: new Abstract: We introduce a finite-size gradient-transport framework for real language-model training, based on five observables (D,z,eta,elta,v_{rel}) that separate

First-Order Efficiency for Probabilistic Value Estimation via A Statistical Viewpoint

arXiv:2605.02827v1 Announce Type: new Abstract: Probabilistic values, including Shapley values and semivalues, provide a model-agnostic framework to attribute the behavior of a black-box model to data

Flow Matching on Symmetric Spaces

arXiv:2605.03588v1 Announce Type: new Abstract: We introduce a general framework for training flow matching models on Riemannian symmetric spaces, a large class of manifolds that includes the sphere,

From prompting to evidence-based translation: A RAG+prompt system for Japanese-Chinese translation and its pedagogical potential

arXiv:2605.03387v1 Announce Type: new Abstract: Large language models perform well on high-resource pairs but are less reliable for Japanese-Chinese sentences containing noun-modifying clause construc

From Sensors to Insight: Rapid, Edge-to-Core Application Development for Sensor-Driven Applications

arXiv:2605.02859v1 Announce Type: cross Abstract: Scientists increasingly rely on sensor-based data, yet transforming raw streams into insights across the edge-to-cloud continuum remains difficult. Pr

Full-Graph vs. Mini-Batch Training: Comprehensive Analysis from a Batch Size and Fan-Out Size Perspective

arXiv:2601.22678v2 Announce Type: replace Abstract: Full-graph and mini-batch Graph Neural Network (GNN) training approaches have distinct system design demands, making it crucial to choose the approp

Fully Automatic Trace Gas Plume Detection

arXiv:2605.03372v1 Announce Type: new Abstract: Future imaging spectrometers will increase data volumes by orders of magnitude, requiring automated detection of trace gas point sources. We present a f

FUS3DMaps: Scalable and Accurate Open-Vocabulary Semantic Mapping by 3D Fusion of Voxel- and Instance-Level Layers

arXiv:2605.03669v1 Announce Type: new Abstract: Open-vocabulary semantic mapping enables robots to spatially ground previously unseen concepts without requiring predefined class sets. Current training

researcharxiv-cs-ro

Gated Subspace Inference for Transformer Acceleration

arXiv:2605.03109v1 Announce Type: new Abstract: A method is presented for accelerating inference in transformer language models by exploiting the low effective rank of the token activation manifold at

GEM-FI: Gated Evidential Mixtures with Fisher Modulation

arXiv:2605.03750v1 Announce Type: new Abstract: Evidential Deep Learning (EDL) enables single-pass uncertainty estimation by predicting Dirichlet evidence, but it can remain overconfident and poorly c

GeoTopoDiff: Learning Geometry--Topology Graph Priors through Boundary-Constrained Mixed Diffusion for Sparse-Slice 3D Porous Reconstruction

arXiv:2605.03764v1 Announce Type: new Abstract: Diffusion-based voxel prior modelling is challenging for the reconstruction of large-scale 3D porous microstructures. Due to the demanding requirements

Graph Convolutional Support Vector Regression for Robust Spatiotemporal Forecasting of Urban Air Pollution

arXiv:2605.03795v1 Announce Type: new Abstract: Urban air quality forecasting is challenging because pollutant concentrations are nonlinear, nonstationary, spatiotemporally dependent, and often affect

GRIFDIR: Graph Resolution-Invariant FEM Diffusion Models in Function Spaces over Irregular Domains

arXiv:2605.03497v1 Announce Type: new Abstract: Score-based diffusion models in infinite-dimensional function spaces provide a mathematically principled framework for modelling function-valued data, o

Highly Adaptive Principal Component Regression

arXiv:2602.10613v2 Announce Type: replace-cross Abstract: The Highly Adaptive Lasso (HAL) is a nonparametric regression method that achieves almost dimension-free convergence rates under minimal smoot

Illumination-Aware Contactless Fingerprint Spoof Detection via Paired Flash-Non-Flash Imaging

arXiv:2603.17679v2 Announce Type: replace Abstract: Contactless fingerprint recognition enables hygienic and convenient biometric authentication but poses new challenges for spoof detection due to the

Imbalanced Classification under Capacity Constraints

arXiv:2605.03289v1 Announce Type: cross Abstract: In many classification settings, the class of primary interest is underrepresented, leading to imbalanced data problems that arise in applications suc

Information Plane Analysis of Binary Neural Networks

arXiv:2605.03636v1 Announce Type: new Abstract: Information plane (IP) analysis has been suggested to study the training dynamics of deep neural networks through mutual information (MI) between inputs

Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy

arXiv:2605.03266v1 Announce Type: cross Abstract: Effective sample size is a standard summary of Markov chain Monte Carlo output, but it is usually attached to scalar or Euclidean summaries chosen by

Investigating the Effects of Different Levels of User Control in an Interactive Educational Recommender System

arXiv:2605.01400v1 Announce Type: cross Abstract: Educational recommender systems (ERSs) are becoming increasingly important in enhancing educational outcomes and personalizing learning experiences by

InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy

arXiv:2507.02974v3 Announce Type: replace-cross Abstract: As major progress in LLM-based long-form text generation enables paradigms such as retrieval-augmented generation (RAG) and inference-time sca

Iterative Finetuning is Mostly Idempotent

arXiv:2605.01130v1 Announce Type: new Abstract: If a model has some behavioral tendency, such as sycophancy or misalignment, and it is trained on its own outputs, will the tendency be amplified in the

Kanade: A Simple Disentangled Tokenizer for Spoken Language Modeling

arXiv:2602.00594v2 Announce Type: replace Abstract: A good language model starts with a good tokenizer. Tokenization is especially important for speech modeling, which must handle continuous signals t

LangPrecip: Language-Aware Multimodal Precipitation Nowcasting

arXiv:2512.22317v2 Announce Type: replace-cross Abstract: Short-term precipitation nowcasting is an inherently uncertain and under-constrained spatiotemporal forecasting problem, especially for rapidl

Large-Scale High-Quality 3D Gaussian Head Reconstruction from Multi-View Captures

arXiv:2605.04035v1 Announce Type: new Abstract: We propose HeadsUp, a scalable feed-forward method for reconstructing high-quality 3D Gaussian heads from large-scale multi-camera setups. Our method em

Learning Generalizable Action Representations via Pre-training AEMG

arXiv:2605.03462v1 Announce Type: new Abstract: A fundamental role in decoding human motor intent and enabling intuitive human-computer interaction is played by electromyography (EMG). However, its ge

Learning to Segment using Summary Statistics and Weak Supervision

arXiv:2605.03059v1 Announce Type: new Abstract: Medical experts often manually segment images to obtain diagnostic statistics and discard the resulting annotations. We aim to train segmentation models

Learning to Theorize the World from Observation

arXiv:2605.03413v1 Announce Type: new Abstract: What does it mean to understand the world? Contemporary world models often operationalize understanding as accurate future prediction in latent or obser