Search: “papers”

ZeroIDIR: Zero-Reference Illumination Degradation Image Restoration with Perturbed Consistency Diffusion Models

arXiv:2605.11435v1 Announce Type: new Abstract: In this paper, we propose a zero-reference diffusion-based framework, named ZeroIDIR, for illumination degradation image restoration, which decouples th

safetyarxiv-cs-cv

13 May 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

A cell-decomposition based path planner for 3D navigation in constrained workspaces

DGX agent

arXiv:2605.10086v1 Announce Type: new Abstract: This paper proposes a cell decomposition algorithm for binary occupancy grids that ensures mutual complete visibility from each cell to at least one adj

researcharxiv-cs-ro

12 May 2026

A Cognitively Grounded Bayesian Framework for Misinformation Susceptibility

arXiv:2605.09483v1 Announce Type: cross Abstract: In this (work in progress) paper, we present Bounded Pragmatic Listener (or BPL), a cognitively grounded Bayesian framework for modelling susceptibili

A Computational Operationalisation of Competing Maturational Theories of Syntactic Development via Statistical Grammar Induction

arXiv:2605.08476v1 Announce Type: new Abstract: This paper is concerned with what intermediate syntactic categories children acquire during first language development, and in what order. Maturational

A low-cost mockup to simulate robotic laser cutting in nuclear decommissioning

arXiv:2605.08947v1 Announce Type: new Abstract: This paper introduces a low-cost experimental mockup to simulate the laser cutting process of containers in nuclear decommissioning. It is composed of a

researcharxiv-cs-ro

A Unified Representation of Neural Networks Architectures

model-releasesarxiv-cs-lg

arXiv:2512.17593v3 Announce Type: replace Abstract: In this paper we consider the limiting case of neural networks (NNs) architectures when the number of neurons in each hidden layer and the number of

Agents

Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery

arXiv:2605.08956v1 Announce Type: new Abstract: A growing body of work pursues AI scientists capable of end-to-end autonomous scientific discovery. This position paper argues that although they alread

agentsarxiv-cs-ai

Can Language Models Analyze Data? Evaluating Large Language Models for Question Answering over Datasets

arXiv:2605.10419v1 Announce Type: cross Abstract: This paper investigates the effectiveness of large language models (LLMs) in answering questions over datasets. We examine their performance in two sc

cantnlp@DravidianLangTech 2026: organic domain adaptation improves multi-class hope speech detection in Tulu

arXiv:2605.09795v1 Announce Type: new Abstract: This paper presents our systems and results for the Hope Speech Detection in Code-Mixed Tulu Language shared task at the Sixth Workshop on Speech, Visio

CapVector: Learning Transferable Capability Vectors in Parametric Space for Vision-Language-Action Models

model-releasesarxiv-cs-cv

arXiv:2605.10903v1 Announce Type: new Abstract: This paper proposes a novel approach to address the challenge that pretrained VLA models often fail to effectively improve performance and reduce adapta

Applications

Causal Discovery for Irregularly Time Series with Consistency Guarantees

arXiv:2507.03310v2 Announce Type: replace-cross Abstract: This paper studies causal discovery in irregularly sampled time series-a key challenge in risk-sensitive domains like finance, healthcare, and

applicationsarxiv-cs-ai

Applications

Causal Discovery Should Embrace the Wisdom of the Crowd

arXiv:2603.02678v3 Announce Type: replace Abstract: This paper argues for recognizing an emerging paradigm of causal learning by wisdom of the crowd. Recent developments in government, industry, and r

applicationsarxiv-cs-lg

Characterizing the Generalization Error of Random Feature Regression with Arbitrary Data-Augmentation

arXiv:2605.10290v1 Announce Type: cross Abstract: This paper aims at analyzing the regularization effect that data augmentation induces on supervised regression methods in the proportional regime, whe

ChatbotManip: A Dataset to Facilitate Evaluation and Oversight of Manipulative Chatbot Behaviour

model-releasesarxiv-cs-cl

arXiv:2506.12090v2 Announce Type: replace Abstract: This paper introduces ChatbotManip, a novel dataset for studying manipulation in Chatbots. It contains simulated generated conversations between a c

Combining Mechanical and Agentic Specification Inference for Move

arXiv:2605.10005v1 Announce Type: cross Abstract: In this paper, we describe early work on a specification inference tool for the Move Prover that combines a weakest-precondition (WP) analysis over Mo

Agents

Consistency as a Testable Property: Statistical Methods to Evaluate AI Agent Reliability

arXiv:2605.10516v1 Announce Type: new Abstract: This paper establishes a rigorous measurement science for AI agent reliability, providing a foundational framework for quantifying consistency under sem

agentsarxiv-cs-ai

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

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

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

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

researcharxiv-cs-cv

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

safetyarxiv-cs-ai

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

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

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

researcharxiv-cs-cv

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

researcharxiv-cs-cv

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

safetyarxiv-cs-ai

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

safetyarxiv-cs-ai

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