Search: “papers”

arXiv:2510.13272v3 Announce Type: replace Abstract: Inspired by the success of reinforcement learning (RL) in Large Language Model (LLM) training for domains like math and code, recent work has begun

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Beyond Static Priors: Dynamic Neural Guidance for Large-Scale Ant Colony Optimization

DGX agent

arXiv:2606.04039v1 Announce Type: cross Abstract: Neural-guided Ant Colony Optimization (ACO) suffers from a fundamental training-inference misalignment: policies are typically trained to generate sta

safetyarxiv-cs-ai

4 Jun 2026

BiasGRPO: Stabilizing Bias Mitigation in High-Variance Reward Landscapes via Group-Relative Policy Optimization

arXiv:2606.04807v1 Announce Type: new Abstract: Mitigating social bias in Large Language Models (LLMs) presents a distinct alignment challenge: unlike verifiable tasks, bias lacks a single ground trut

Blessing from Human-AI Interaction: Super Reinforcement Learning in Confounded Environments

arXiv:2209.15448v3 Announce Type: replace Abstract: As AI becomes more prevalent throughout society, effective methods of integrating humans and AI systems that leverage their respective strengths and

safetyarxiv-cs-lg

Tutorials

Can Crowdsourcing Survive the LLM Era? A Community Survey on Human Data Collection

arXiv:2606.04924v1 Announce Type: new Abstract: The widespread use of Large Language Models (LLMs) as writing tools challenges the validity of crowdsourced data, as crowdworkers may outsource tasks to

tutorialsarxiv-cs-cl

Can Generalist Agents Automate Data Curation?

model-releasesarxiv-cs-ai

arXiv:2606.04261v1 Announce Type: new Abstract: Curating training data is among the most consequential yet labor-intensive parts of modern AI development: practitioners iteratively propose, implement,

Can Large Language Models Generalize Procedures Across Representations?

model-releasesarxiv-cs-cl

arXiv:2602.03542v2 Announce Type: replace Abstract: Large language models (LLMs) are trained and tested extensively on symbolic representations such as code and graphs, yet real-world user tasks are o

Cone-Compatible Monge Geometry for High-Dimensional Ordered Optimal Transport

arXiv:2606.04695v1 Announce Type: new Abstract: High-dimensional optimal transport is seldom available in closed form. The one-dimensional case is exceptional because the order of the real line is com

Culturally Grounded Personas in Large Language Models: Characterization and Alignment with Socio-Psychological Value Frameworks

arXiv:2601.22396v2 Announce Type: replace-cross Abstract: Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accura

Agents

Description-Code Inconsistency in Real-world MCP Servers: Measurement, Detection, and Security Implications

arXiv:2606.04769v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has emerged as a critical standard empowering Large Language Models (LLMs) to utilize external tools. In this ecosyst

agentsarxiv-cs-ai

Differentially Private Joint Independence Test

arXiv:2503.18721v3 Announce Type: replace-cross Abstract: Identification of joint dependence among several random vectors plays an important role in many statistical applications, where the data may c

Local Ai

DiverAge: Reliable Pluralistic Face Aging with Cross-Age Identity Relation Guidance

arXiv:2606.04881v1 Announce Type: cross Abstract: Face aging plays an important role in long-term biometric analysis, cross-age identity verification, and forensic identity analysis. Since the same su

local-aiarxiv-cs-ai

DPM++: Dynamic Masked Metric Learning for Occluded Person Re-identification

arXiv:2605.06637v2 Announce Type: replace Abstract: Although person re-identification has made impressive progress, occlusion caused by obstacles remains an unsettled issue in real applications. The d

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Local Ai

Enhancing MedSAM with a Lightweight Box Predictor for Medical Image Segmentation

arXiv:2606.04705v1 Announce Type: cross Abstract: Semantic segmentation in medical imaging is a critical yet challenging task due to data scarcity and high variability across modalities. While foundat

local-aiarxiv-cs-ai

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction

model-releasesarxiv-cs-ai

arXiv:2602.23312v3 Announce Type: replace-cross Abstract: Leader-follower interaction is an important paradigm in human-robot interaction (HRI). Yet, assigning roles in real time remains challenging f

Explaining a probabilistic prediction on the simplex with Shapley compositions

arXiv:2408.01382v3 Announce Type: replace Abstract: Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of e

Fast Cubical Persistent Homology on 2D and 3D Images via Union-Find, Pruning, and Lookup Tables

arXiv:2606.04801v1 Announce Type: new Abstract: We present Flash Cubical, a highly efficient computation of cubical persistence on a V-filtration for 2D and 3D images over F_2. The implementation is b

Flatness and Generalization: Learning Multi-Index Models with Homogeneous Neural Networks

arXiv:2606.04429v1 Announce Type: cross Abstract: A common heuristic used to explain the generalization of first-order gradient methods on non-convex neural networks is that 'flat interpolators genera

Tutorials

Geometry-Preserving Encoder/Decoder in Latent Generative Models

arXiv:2501.09876v3 Announce Type: replace-cross Abstract: Generative modeling aims to generate new data samples that resemble a given dataset. When using diffusion models for this task, one of the mai

tutorialsarxiv-cs-lg

GlossAssist -- A Tool to Simplify Corpus Creation and Study the Effect of NLP Models in Low-Resource Documentation Settings

arXiv:2606.04367v1 Announce Type: new Abstract: Interlinear glossed text (IGT) is the standard format for linguistic annotation in language documentation. Producing it manually, however, is often slow

researcharxiv-cs-cl

Graph-Guided Universum Learning in Generalized Eigenvalue Proximal SVMs for Alzheimer's Disease Classification

arXiv:2606.04699v1 Announce Type: cross Abstract: Early and accurate detection of Alzheimer's disease (AD) is important for timely intervention and disease management. Generalized Eigenvalue Proximal

researcharxiv-cs-ai

Gravity-Aware Hierarchical Routing for Lightweight SensorLLM on Human Activity Recognition

model-releasesarxiv-cs-ai

arXiv:2606.04019v1 Announce Type: cross Abstract: Recent studies on sensor-language alignment have shown that two-stage frameworks can improve the semantic modeling ability of wearable-sensor human ac

Handwriting Extraction and Analysis of Signature Lists in Swiss Popular Initiatives

arXiv:2606.05018v1 Announce Type: new Abstract: Popular initiatives and referendums are central to Swiss democracy, yet the validation of handwritten signature lists remains a labor-intensive manual p

How Users Understand Robot Foundation Model Performance through Task Success Rates and Beyond

arXiv:2602.03920v2 Announce Type: replace Abstract: Robot Foundation Models (RFMs) represent a promising approach to developing general-purpose home robots. Given the broad capabilities of RFMs, users

researcharxiv-cs-ro

Identifying and Correcting Label Noise for Robust GNNs via Influence Contradiction

model-releasesarxiv-cs-lg

arXiv:2601.17469v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have shown remarkable capabilities in learning from graph-structured data with various applications such as social anal

IMPose: Interactive Multi-person Pose Estimation with Dynamic Correction Propagation

arXiv:2606.04480v1 Announce Type: new Abstract: High-quality dynamic human pose annotation equips AI with precise motion kinematics to enable human behavior mastery, yet remains labor-intensive and ti

Inclusion-of-Thoughts: Mitigating Preference Instability via Purifying the Decision Space

arXiv:2604.04944v2 Announce Type: replace-cross Abstract: Multiple-choice questions (MCQs) are widely used to evaluate large language models (LLMs). However, LLMs remain vulnerable to the presence of

researcharxiv-cs-ai

Knockoffs-based False Discovery Rate Control and Simplification for Deep Neural Networks

arXiv:2606.04404v1 Announce Type: cross Abstract: The deep neural network is a widely used framework in machine learning that has been widely applied in various fields. However, deep neural networks o

Learning Empirically Admissible Neural Heuristics for Combinatorial Search

arXiv:2606.04860v1 Announce Type: cross Abstract: Finding optimal solution paths for combinatorial puzzles like the Rubik's Cube, sliding tile puzzles, and Lights Out remains a classical challenge in

Learning symplectic model reduction based on a approximation theorem of symplectic embeddings

arXiv:2606.04623v1 Announce Type: new Abstract: High-dimensional Hamiltonian systems play a central role in many scientific and engineering disciplines, with dynamics evolving on symplectic manifolds.

Leaving aside the question of consciousness, the Ted Chiang piece has a reasonable point about moral atrophy if you let AI make choices. But…

model-releasesethan-mollick--x

Leaving aside the question of consciousness, the Ted Chiang piece has a reasonable point about moral atrophy if you let AI make choices. But it is also interesting in light of the fact that repeated r

LMM-IR: Large-Scale Netlist-Aware Multimodal Framework for Static IR-Drop Prediction

arXiv:2511.12581v2 Announce Type: replace Abstract: Static IR drop analysis is a fundamental and critical task in the field of chip design. Nevertheless, this process can be quite time-consuming, pote

Local Clustering on Complex Graphs and Complex Hypergraphs

arXiv:2412.03008v2 Announce Type: replace-cross Abstract: Local/seeded clustering aims to find a compact cluster near the given starting instances. While most existing studies on graph clustering assu

applicationsarxiv-cs-lg

Local Ai

MAD: Mapping-Aware World Models for Agile Quadrotor Flight

arXiv:2606.04534v1 Announce Type: new Abstract: Agile quadrotor flight in cluttered scenes requires more than a reactive mapping from a depth image to a control command: the vehicle must remember whic

local-aiarxiv-cs-ro

Tutorials

Measuring What Matters: Synthetic Benchmarks for Concept Bottleneck Models

arXiv:2606.04326v1 Announce Type: cross Abstract: Concept bottleneck models predict outcomes from high-level concepts detected in inputs. Although concepts provide a simple way to reap benefits from i

tutorialsarxiv-cs-ai

Multi-Camera AR Guidance System for Surgical Instrument Handling and Assembly: Investigating Workload and Efficiency

arXiv:2606.04992v1 Announce Type: new Abstract: The handling and assembly of instruments during surgery imposes high cognitive demands on scrub nurses, particularly when instruments are unfamiliar. We

applicationsarxiv-cs-cv

Neural Radiated-Noise Fields for Unmanned Underwater Vehicle Noise Spectrum Prediction in Three-Dimensional Scenes

arXiv:2606.04008v1 Announce Type: cross Abstract: Radiated noise in unmanned underwater vehicles (UUVs) is an important indicator for characterizing acoustic signatures and evaluating platform perform

researcharxiv-cs-ai

On the Relationship Between CoCoA and ADMM for Distributed Empirical Risk Minimization

model-releasesarxiv-cs-lg

arXiv:2502.00470v3 Announce Type: replace-cross Abstract: Distributed empirical risk minimization (ERM) is often studied through two influential yet seemingly separate families of methods: CoCoA-type

PE-MHL: Physics-Encoded Modular Hybrid Layers for Scalable Learning of Complex Systems

model-releasesarxiv-cs-lg

arXiv:2606.04290v1 Announce Type: new Abstract: Hybrid models that combine physics-based and data-driven components have shown strong potential for achieving accuracy and interpretability in control a

Policy Gradient for Continuous-Time Robust Markov Decision Processes

arXiv:2606.04335v1 Announce Type: new Abstract: The framework of robust Markov decision processes (RMDPs) allows the design of reinforcement learning agents that satisfy performance guarantees under w

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Agents

Position: Deployed Reinforcement Learning should be Continual

arXiv:2606.04029v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has received increasing attention and adoption in real-world use cases. Most of these systems follow a train-then-fix para

agentsarxiv-cs-ai

Prediction Under Imperfect Compression: A Theory of Approximate MDL

arXiv:2606.04834v1 Announce Type: new Abstract: Minimum Description Length (MDL) formalizes the principle of Occam's razor by optimizing the total description length: L(model)+L(data | model). For seq

Preserving Data Privacy in Learning Causal Structure with Fully Homomorphic Encryption

arXiv:2606.05129v1 Announce Type: cross Abstract: Preserving data privacy is an important topic in structural data management and data mining. However, the issue of privacy leakage in distributed caus

Query-based Cross-Modal Projector Bolstering Mamba Multimodal LLM

arXiv:2606.04719v1 Announce Type: new Abstract: The Transformer's quadratic complexity with input length imposes an unsustainable computational load on large language models (LLMs). In contrast, the S

researcharxiv-cs-cl

Reconciling Causality and Non-Equilibrium Thermodynamics with Hamiltonian Causal Models

arXiv:2606.04822v1 Announce Type: new Abstract: Causal modeling of physical temporal phenomena must handle interventions that act along trajectories, nonstationary induced laws, path-dependent effects

applicationsarxiv-cs-lg

ReConFuse: Reconstruction-Error Guided Semantic Fusion for AI-Generated Video Detection

arXiv:2606.04706v1 Announce Type: new Abstract: AI-generated videos are becoming increasingly realistic, raising serious concerns about misinformation, content authenticity, and media trust. Reliable

Reflection Separation from a Single Image via Joint Latent Diffusion

arXiv:2606.04107v1 Announce Type: new Abstract: Single-image reflection separation is highly challenging under extreme conditions like glare or weak reflections. Existing methods often struggle to rec

applicationsarxiv-cs-cv

Reproducing, Analyzing, and Detecting Reward Hacking in Rubric-Based Reinforcement Learning

arXiv:2606.04923v1 Announce Type: cross Abstract: Rubric-based reinforcement learning (RL) uses an LLM-as-a-Judge (LaaJ) to score model outputs according to rubrics as rewards. However, policy models