Search: “papers”

Cross-Domain Lossy Compression via Constrained Minimum Entropy Coupling

arXiv:2605.09833v1 Announce Type: cross Abstract: This paper studies cross-domain lossy compression through the lens of minimum entropy coupling (MEC) with rate and classification constraints. In this

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Research

DECO-MWE: building a linguistic resource of Korean multiword expressions for feature-based sentiment analysis

DGX agent

arXiv:2605.10295v1 Announce Type: new Abstract: This paper aims to construct a linguistic resource of Korean Multiword Expressions for Feature-Based Sentiment Analysis (FBSA): DECO-MWE. Dealing with m

researcharxiv-cs-cl

12 May 2026

Deep Dreams Are Made of This: Visualizing Monosemantic Features in Diffusion Models

arXiv:2605.08218v1 Announce Type: cross Abstract: This paper proposes latent visualization by optimization (LVO), a mechanistic interpretability technique that extends feature visualization by optimiz

Deep-ICE: the first globally optimal algorithm for minimizing 0-1 loss in two-layer ReLU and maxout networks

arXiv:2505.05740v3 Announce Type: replace Abstract: This paper introduces the first globally optimal algorithm for the empirical risk minimization problem of two-layer maxout and ReLU networks, i.e.,

Differentially Private Sampling from Distributions via Wasserstein Projection

arXiv:2605.10015v1 Announce Type: cross Abstract: In this paper, we study the problem of sampling from a distribution under the constraint of differential privacy (DP). Prior works measure the utility

Distributional Reinforcement Learning via the Cramer Distance

arXiv:2605.08104v1 Announce Type: new Abstract: This paper explores the application of the Soft Actor-Critic (SAC) algorithm within a Distributional Reinforcement Learning setting and introduces an im

Empowering VLMs for Few-Shot Multimodal Time Series Classification via Tailored Agentic Reasoning

arXiv:2605.09395v1 Announce Type: new Abstract: In this paper, we propose the first VLnderline{extbf{M}} nderline{extbf{a}}gentic nderline{extbf{r}}easoning framework for few-nderline{extbf{s}}hot mul

Hardware

Energy Consumption of Dataframe Libraries for End-to-End Deep Learning Pipelines:A Comparative Analysis

arXiv:2511.08644v3 Announce Type: replace-cross Abstract: This paper presents a detailed comparative analysis of the performance of three major Python data manipulation libraries - Pandas, Polars, and

hardwarearxiv-cs-ai

Exact Unlearning from Proxies Induces Closeness Guarantees on Approximate Unlearning

arXiv:2605.10680v1 Announce Type: new Abstract: This paper proposes a paradigm shift linking machine unlearning directly to the structure of the data distributions rather than a mere update of the neu

FinMoji: A Framework for Emoji-driven Sentiment Analysis in Financial Social Media

arXiv:2605.09469v1 Announce Type: new Abstract: This paper explores the use of emojis in financial sentiment analysis, focusing on the social media platform StockTwits. Emojis, increasingly prevalent

researcharxiv-cs-cl

Local Ai

Fully Decentralized Cooperative Multi-Agent Reinforcement Learning is A Context Modeling Problem

arXiv:2509.15519v2 Announce Type: replace Abstract: This paper studies fully decentralized cooperative multi-agent reinforcement learning, where each agent solely observes the states, its local action

local-aiarxiv-cs-lg

Gate-and-Merge: Zero-shot Compositional Personalization of Vision Language Models

arXiv:2605.08702v1 Announce Type: cross Abstract: This paper tackles compositional personalization of vision-language models (VLMs). In this problem, multiple user-defined concepts must be recognized

Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing

arXiv:2605.10582v1 Announce Type: cross Abstract: This paper proposes a guaranteed defense method for large language models (LLMs) to safeguard against jailbreaking attacks. Drawing inspiration from t

ICT-NLP at SemEval-2026 Task 3: Less Is More -- Multilingual Encoder with Joint Training and Adaptive Ensemble for Dimensional Aspect Sentiment Regression

arXiv:2605.10560v1 Announce Type: new Abstract: This paper describes our system to SemEval-2026 Task 3 Track A Subtask 1 on Dimensional Aspect Sentiment Regression (DimASR). We propose a lightweight a

researcharxiv-cs-cl

Local Ai

Initiation of Interaction Detection Framework using a Nonverbal Cue for Human-Robot Interaction

arXiv:2605.10087v1 Announce Type: new Abstract: This paper describes an initiation of interaction(IoI) detection framework without keywords for human-robot interaction(HRI) based on audio and vision s

local-aiarxiv-cs-cv

Learning to Sparsify Stochastic Linear Bandits

model-releasesarxiv-cs-lg

arXiv:2605.10151v1 Announce Type: new Abstract: This paper addresses the problem of learning to sparsify stochastic linear bandits, where a decision-maker sequentially selects actions from a high-dime

MicroViTv2: Beyond the FLOPS for Edge Energy-Friendly Vision Transformers

arXiv:2605.10148v1 Announce Type: new Abstract: The Vision Transformer (ViT) achieves remarkable accuracy across visual tasks but remains computationally expensive for edge deployment. This paper pres

MOBIUS: A Multi-Modal Bipedal Robot that can Walk, Crawl, Climb, and Roll

arXiv:2511.01774v3 Announce Type: replace Abstract: This paper presents the MOBIUS platform, a bipedal robot capable of walking, crawling, climbing, and rolling. MOBIUS features four limbs, two 6-DoF

researcharxiv-cs-ro

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning

arXiv:2605.09364v1 Announce Type: new Abstract: This paper investigates robust representation learning in offline goal-conditioned reinforcement learning (GCRL). Particularly in sparse reward scenario

safetyarxiv-cs-lg

NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation

arXiv:2605.10813v1 Announce Type: new Abstract: LLM-powered multi-agent systems can now automate the full research pipeline from ideation to paper writing, but a fundamental question remains: automati

Nearly-Optimal Algorithm for Adversarial Kernelized Bandits

arXiv:2605.10299v1 Announce Type: new Abstract: This paper studies kernelized bandits (also known as Gaussian process bandits) in an adversarial environment, where the reward functions in a known repr

Applications

Neural Variance-aware Dueling Bandits with Deep Representation and Shallow Exploration

arXiv:2506.01250v2 Announce Type: replace Abstract: In this paper, we address the contextual dueling bandit problem by proposing variance-aware algorithms that leverage neural networks to approximate

applicationsarxiv-cs-lg

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning

arXiv:2605.08221v1 Announce Type: cross Abstract: This paper presents NoisyCoconut, a novel inference-time method that enhances large language model (LLM) reliability by manipulating internal represen

OCP-GN: A Scalable Second-order Optimizer for Stochastic Optimization

arXiv:2512.24552v2 Announce Type: replace Abstract: This paper proposes a novel second-order optimization algorithm based on the Optimal Control Principle (OCP), applicable to large-scale optimization

Quantitative Error Feedback for Quantization Noise Reduction of Filtering over Graphs

arXiv:2506.01404v2 Announce Type: replace Abstract: This paper introduces an innovative error feedback framework designed to mitigate quantization noise in distributed graph filtering, where communica

Re-Triggering Safeguards within LLMs for Jailbreak Detection

arXiv:2605.10611v1 Announce Type: cross Abstract: This paper proposes a jailbreaking prompt detection method for large language models (LLMs) to defend against jailbreak attacks. Although recent LLMs

RUBEN: Rule-Based Explanations for Retrieval-Augmented LLM Systems

arXiv:2605.10862v1 Announce Type: new Abstract: This paper demonstrates RUBEN, an interactive tool for discovering minimal rules to explain the outputs of retrieval-augmented large language models (LL

safetyarxiv-cs-cl

Safe Exploration for Nonlinear Processes Using Online Gaussian Process Learning

arXiv:2605.09772v1 Announce Type: cross Abstract: This paper proposes a safe data-driven control framework for nonlinear systems with partially known dynamics. The method ensures stability and constra

safetyarxiv-cs-ro

SCALAR: A Neurosymbolic Framework for Automated Conjecture and Reasoning in Quantum Circuit Analysis

arXiv:2605.10327v1 Announce Type: cross Abstract: In this paper, we present SCALAR (Symbolic Conjecture and LLM-Assisted Reasoning), a neurosymbolic framework for automated conjecture generation in qu

Sink vs. diagonal patterns as mechanisms for attention switch and oversmoothing prevention

arXiv:2605.08453v1 Announce Type: cross Abstract: This paper studies the role of sinks and diagonal patterns as attention switch and anti-oversmoothing mechanisms. We analyze geometric conditions unde

Sliding Window Informative Canonical Correlation Analysis

arXiv:2507.17921v2 Announce Type: replace-cross Abstract: Canonical correlation analysis (CCA) is a technique for finding correlated sets of features between two datasets. In this paper, we propose a

Stability of the Monge Map in Semi-Dual Optimal Transport

arXiv:2605.05569v2 Announce Type: replace-cross Abstract: This paper shows that the semi-dual formulation of the optimal transport problem has a degenerate saddle-point structure, and that its numeric

Sufficient conditions for a Heuristic Rating Estimation Method application

arXiv:2605.08991v1 Announce Type: new Abstract: A series of papers has introduced the Heuristic Rating Estimation method, which evaluates a set of alternatives based on pairwise comparisons and the we

Switching-Geometry Analysis of Deflated Q-Value Iteration

arXiv:2605.10811v1 Announce Type: cross Abstract: This paper develops a joint spectral radius (JSR) framework for analyzing rank-one deflated Q-value iteration (Q-VI) in discounted Markov decision pro

The Direct Integration Theorem: A Rigorous Framework for Consistent Discrete Solutions of the Inverse Radon Problem

arXiv:2605.09020v1 Announce Type: new Abstract: This paper presents a novel Direct Integration Theorem (DIT), derived as a non-trivial corollary of the classical Central Slice Theorem (CST). The DIT p

The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints

arXiv:1706.00476v4 Announce Type: replace-cross Abstract: In this paper, we propose a low-rank coordinate descent approach to structured semidefinite programming with diagonal constraints. The approac

Transfer Learning for Dead Fuel Moisture Prediction Using Time-Warping Recurrent Neural Networks

arXiv:2605.08379v1 Announce Type: cross Abstract: This paper proposes a time-warping transfer learning method, a technique for temporally rescaling the learned dynamics of a recurrent neural network (

Applications

Transformer autoencoder with local attention for sparse and irregular time series with application on risk estimation

arXiv:2605.08914v1 Announce Type: cross Abstract: This paper introduces a framework specifically designed for sparse and irregular time series {risk estimation}. It is based on a Transformer Autoencod

applicationsarxiv-cs-ai

Universal Feature Selection with Noisy Observations and Weak Symmetry Conditions

arXiv:2605.09396v1 Announce Type: cross Abstract: This paper relaxes the restrictive symmetry conditions adopted in [4], [5] and extends their universal feature selection framework to accommodate nois

Unpredictability dissociates from structured control in language agents

arXiv:2605.09692v1 Announce Type: new Abstract: Unpredictable behavior is often taken as evidence of control, yet stochastic dispersion and structured action control need not coincide. This paper test

UTS at PsyDefDetect: Multi-Agent Councils and Absence-Based Reasoning for Defense Mechanism Classification

arXiv:2605.09769v1 Announce Type: new Abstract: This paper describes our system for classifying psychological defense mechanisms in emotional support dialogues using the Defense Mechanism Rating Scale

Tutorials

VeloGauss: Learning Physically Consistent Gaussian Velocity Fields from Videos

arXiv:2605.10567v1 Announce Type: new Abstract: In this paper, we aim to jointly model the geometry, appearance, and physical information of 3D scenes solely from dynamic multi-view videos, without re

tutorialsarxiv-cs-cv

X-Voice: Enabling Everyone to Speak 30 Languages via Zero-Shot Cross-Lingual Voice Cloning

arXiv:2605.05611v2 Announce Type: replace-cross Abstract: In this paper, we present X-Voice, a 0.4B multilingual zero-shot voice cloning model that clones arbitrary voices and enables everyone to spea

xApp Empowered Resource Management for Non-Terrestrial Users in 5G O-RAN Networks

arXiv:2605.10704v1 Announce Type: cross Abstract: This paper introduces a proactive Unmanned Aerial Vehicle (UAV) mobility management xApp for Open Radio Access Network (O-RAN) Near Real-Time Radio In

researcharxiv-cs-ro

YEZE at SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization via Heterogeneous Ensembling

arXiv:2605.06231v2 Announce Type: replace Abstract: This paper presents our system for SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization, which identifies p

researcharxiv-cs-cl

6D Pose Estimation via Keypoint Heatmap Regression with RGB-D Residual Neural Networks

arXiv:2605.08059v1 Announce Type: new Abstract: In this paper, we propose a modular framework for 6D pose estimation based on keypoint heatmap regression. Our approach combines YOLOv10m for object det

11 May 2026

Local Ai

A Closed-Form Upper Bound for Admissible Learning-Rate Steps in Belief-Space Dynamics

arXiv:2605.06741v1 Announce Type: new Abstract: Learning-rate steps are usually treated as hyperparameters. This paper isolates a local beliefspace calculation: when an update is modeled as a projecte

local-aiarxiv-cs-lg

11 May 2026

Actor-Critic with Active Importance Sampling