Search: “models”

Construction of a Battery Research Knowledge Graph using a Global Open Catalog

arXiv:2604.20241v1 Announce Type: new Abstract: Battery research is a rapidly growing and highly interdisciplinary field, making it increasingly difficult to track relevant expertise and identify pote

researcharxiv-cs-cl

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Research

CrackForward: Context-Aware Severity Stage Crack Synthesis for Data Augmentation

DGX agent

arXiv:2604.19941v1 Announce Type: new Abstract: Reliable crack detection and segmentation are vital for structural health monitoring, yet the scarcity of well-annotated data constitutes a major challe

researcharxiv-cs-cv

23 Apr 2026

CreativeGame:Toward Mechanic-Aware Creative Game Generation

arXiv:2604.19926v1 Announce Type: new Abstract: Large language models can generate plausible game code, but turning this capability into iterative creative improvement remains difficult. In practice,

Efficient Multi-Cohort Inference for Long-Term Effects and Lifetime Value in A/B Testing with User Learning

arXiv:2604.20777v1 Announce Type: new Abstract: In streaming platforms churn is extremely costly, yet A/B tests are typically evaluated using outcomes observed within a limited experimental horizon. E

Efficient Symbolic Computations for Identifying Causal Effects

arXiv:2604.20516v1 Announce Type: cross Abstract: Determining identifiability of causal effects from observational data under latent confounding is a central challenge in causal inference. For linear

tutorialsarxiv-cs-lg

Emergence Transformer: Dynamical Temporal Attention Matters

arXiv:2604.19816v1 Announce Type: new Abstract: The Transformer, a breakthrough architecture in artificial intelligence, owes its success to the attention mechanism, which utilizes long-range interact

Enhancing ASR Performance in the Medical Domain for Dravidian Languages

arXiv:2604.19797v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) for low-resource Dravidian languages like Telugu and Kannada faces significant challenges in specialized medical do

tutorialsarxiv-cs-ai

ETac: A Lightweight and Efficient Tactile Simulation Framework for Learning Dexterous Manipulation

arXiv:2604.20295v1 Announce Type: new Abstract: Tactile sensors are increasingly integrated into dexterous robotic manipulators to enhance contact perception. However, learning manipulation policies t

safetyarxiv-cs-ro

FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels

arXiv:2604.20825v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative model training without sharing raw data; however, the presence of noisy labels across distributed client

Applications

From Nodes to Narratives: Explaining Graph Neural Networks with LLMs and Graph Context

arXiv:2508.07117v3 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have emerged as powerful tools for learning over structured data, including text-attributed graphs (TAGs), which are co

applicationsarxiv-cs-lg

From Noise to Signal to Selbstzweck: Reframing Human Label Variation in the Era of Post-training in NLP

arXiv:2510.12817v3 Announce Type: replace-cross Abstract: Human Label Variation (HLV) refers to legitimate disagreement in annotation that reflects the diversity of human perspectives rather than mere

HaS: Accelerating RAG through Homology-Aware Speculative Retrieval

arXiv:2604.20452v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) at inference by retrieving external documents as c

agentsarxiv-cs-cl

Improving Molecular Force Fields with Minimal Temporal Information

arXiv:2604.19806v1 Announce Type: cross Abstract: Accurate prediction of energy and forces for 3D molecular systems is one of fundamental challenges at the core of AI for Science applications. Many po

Investigation of cardinality classification for bacterial colony counting using explainable artificial intelligence

arXiv:2604.20026v1 Announce Type: new Abstract: Automatic bacterial colony counting is a highly sought-after technology in modern biological laboratories because it eliminates manual counting effort.

researcharxiv-cs-cv

Is Four Enough? Automated Reasoning Approaches and Dual Bounds for Condorcet Dimensions of Elections

arXiv:2604.19851v1 Announce Type: cross Abstract: In an election where n voters rank m candidates, a Condorcet winning set is a committee of k candidates such that for any outside candidate, a majorit

JTPRO: A Joint Tool-Prompt Reflective Optimization Framework for Language Agents

arXiv:2604.19821v1 Announce Type: new Abstract: Large language model (LLM) agents augmented with external tools often struggle as number of tools grow large and become domain-specific. In such setting

LLMs Can Get 'Brain Rot': A Pilot Study on Twitter/X

arXiv:2510.13928v2 Announce Type: replace-cross Abstract: We propose and test the LLM Brain Rot Hypothesis: continual exposure to junk web text induces lasting cognitive decline in large language mode

Lucky High Dynamic Range Smartphone Imaging

arXiv:2604.19976v1 Announce Type: new Abstract: While the human eye can perceive an impressive twenty stops of dynamic range, smartphone camera sensors remain limited to about twelve stops despite dec

researcharxiv-cs-cv

Multi-Armed Bandits With Machine Learning-Generated Surrogate Rewards

arXiv:2506.16658v2 Announce Type: replace-cross Abstract: Multi-armed bandit (MAB) is a widely adopted framework for sequential decision-making under uncertainty. Traditional bandit algorithms rely so

Multi-Objective Reinforcement Learning for Generating Covalent Inhibitor Candidates

arXiv:2604.20019v1 Announce Type: new Abstract: Rational design of covalent inhibitors requires simultaneously optimizing multiple properties, such as binding affinity, target selectivity, or electrop

Multi-Perspective Evidence Synthesis and Reasoning for Unsupervised Multimodal Entity Linking

arXiv:2604.20283v1 Announce Type: new Abstract: Multimodal Entity Linking (MEL) is a fundamental task in data management that maps ambiguous mentions with diverse modalities to the multimodal entities

researcharxiv-cs-cl

NanoCockpit: Performance-optimized Application Framework for AI-based Autonomous Nanorobotics

arXiv:2601.07476v2 Announce Type: replace Abstract: Autonomous nano-drones, powered by vision-based tiny machine learning (TinyML) models, are a novel technology gaining momentum thanks to their broad

agentsarxiv-cs-ro

Occupancy Reward Shaping: Improving Credit Assignment for Offline Goal-Conditioned Reinforcement Learning

arXiv:2604.20627v1 Announce Type: new Abstract: The temporal lag between actions and their long-term consequences makes credit assignment a challenge when learning goal-directed behaviors from data. G

On the definition and importance of interpretability in scientific machine learning

arXiv:2505.13510v3 Announce Type: replace Abstract: Though neural networks trained on large datasets have been successfully used to describe and predict many physical phenomena, there is a sense among

PASTA: A Patch-Agnostic Twofold-Stealthy Backdoor Attack on Vision Transformers

arXiv:2604.20047v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved remarkable success across vision tasks, yet recent studies show they remain vulnerable to backdoor attacks. Exi

researcharxiv-cs-cv

Physics-Conditioned Synthesis of Internal Ice-Layer Thickness for Incomplete Layer Traces

arXiv:2604.20783v1 Announce Type: new Abstract: Internal ice layers imaged by radar provide key evidence of snow accumulation and ice dynamics, but radar-derived layer boundary observations are often

tutorialsarxiv-cs-lg

Physics-Guided Dimension Reduction for Simulation-Free Operator Learning of Stiff Differential--Algebraic Systems

arXiv:2604.19930v1 Announce Type: new Abstract: Neural surrogates for stiff differential-algebraic equations (DAEs) face two key challenges: soft-constraint methods leave algebraic residuals that stif

R2IF: Aligning Reasoning with Decisions via Composite Rewards for Interpretable LLM Function Calling

arXiv:2604.20316v1 Announce Type: new Abstract: Function calling empowers large language models (LLMs) to interface with external tools, yet existing RL-based approaches suffer from misalignment betwe

SignDATA: Data Pipeline for Sign Language Translation

arXiv:2604.20357v1 Announce Type: cross Abstract: Sign-language datasets are difficult to preprocess consistently because they vary in annotation schema, clip timing, signer framing, and privacy const

safetyarxiv-cs-cl

SolidCoder: Bridging the Mental-Reality Gap in LLM Code Generation through Concrete Execution

arXiv:2604.19825v1 Announce Type: cross Abstract: State-of-the-art code generation frameworks rely on mental simulation, where LLMs internally trace execution to verify correctness. We expose a fundam

SphUnc: Hyperspherical Uncertainty Decomposition and Causal Identification via Information Geometry

arXiv:2603.01168v2 Announce Type: replace-cross Abstract: Reliable decision-making in complex multi-agent systems requires calibrated predictions and interpretable uncertainty. We introduce SphUnc, a

Hardware

Stream-CQSA: Avoiding Out-of-Memory in Attention Computation via Flexible Workload Scheduling

arXiv:2604.20819v1 Announce Type: new Abstract: The scalability of long-context large language models is fundamentally limited by the quadratic memory cost of exact self-attention, which often leads t

hardwarearxiv-cs-lg

The effect of the number of parameters and the number of local feature patches on loss landscapes in distributed quantum neural networks

arXiv:2504.19239v2 Announce Type: replace-cross Abstract: Quantum neural networks hold promise for tackling computationally challenging tasks that are intractable for classical computers. However, the

The Tool-Overuse Illusion: Why Does LLM Prefer External Tools over Internal Knowledge?

arXiv:2604.19749v1 Announce Type: new Abstract: Equipping LLMs with external tools effectively addresses internal reasoning limitations. However, it introduces a critical yet under-explored phenomenon

TriEx: A Game-based Tri-View Framework for Explaining Internal Reasoning in Multi-Agent LLMs

arXiv:2604.20043v1 Announce Type: cross Abstract: Explainability for Large Language Model (LLM) agents is especially challenging in interactive, partially observable settings, where decisions depend o

Visual Reasoning through Tool-supervised Reinforcement Learning

arXiv:2604.19945v1 Announce Type: new Abstract: In this paper, we investigate the problem of how to effectively master tool-use to solve complex visual reasoning tasks for Multimodal Large Language Mo

agentsarxiv-cs-cv

Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation

arXiv:2604.20749v1 Announce Type: new Abstract: Situated conversational recommendation (SCR), which utilizes visual scenes grounded in specific environments and natural language dialogue to deliver co

Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment

arXiv:2601.14249v4 Announce Type: replace Abstract: Long chain-of-thought (CoT) trajectories provide rich supervision signals for distilling reasoning from teacher to student LLMs. However, both prior

safetyarxiv-cs-cl

Working Memory Constraints Scaffold Learning in Transformers under Data Scarcity

arXiv:2604.20789v1 Announce Type: cross Abstract: We investigate the integration of human-like working memory constraints into the Transformer architecture and implement several cognitively inspired a

A Dual Perspective on Synthetic Trajectory Generators: Utility Framework and Privacy Vulnerabilities

arXiv:2604.19653v1 Announce Type: new Abstract: Human mobility data are used in numerous applications, ranging from public health to urban planning. Human mobility is inherently sensitive, as it can c

Accelerating Optimization and Machine Learning through Decentralization

arXiv:2604.19518v1 Announce Type: new Abstract: Decentralized optimization enables multiple devices to learn a global machine learning model while each individual device only has access to its local d

tutorialsarxiv-cs-lg

Age-Dependent Heterogeneity in the Association Between Physical Activity and Mental Distress: A Causal Machine Learning Analysis of 3.2 Million U.S. Adults

arXiv:2604.19066v1 Announce Type: new Abstract: Physical activity (PA) is widely recognized as protective against mental distress, yet whether this benefit varies systematically across population subg

AI-Enabled Image-Based Hybrid Vision/Force Control of Tendon-Driven Aerial Continuum Manipulators

arXiv:2604.18961v1 Announce Type: cross Abstract: This paper presents an AI-enabled cascaded hybrid vision/force control framework for tendon-driven aerial continuum manipulators based on constant-str

agentsarxiv-cs-cv

ASVSim (AirSim for Surface Vehicles): A High-Fidelity Simulation Framework for Autonomous Surface Vehicle Research

arXiv:2506.22174v2 Announce Type: replace-cross Abstract: The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway

AutoAWG: Adverse Weather Generation with Adaptive Multi-Controls for Automotive Videos

arXiv:2604.18993v1 Announce Type: cross Abstract: Perception robustness under adverse weather remains a critical challenge for autonomous driving, with the core bottleneck being the scarcity of real-w

Autonomous UAV Pipeline Near-proximity Inspection via Disturbance-Aware Predictive Visual Servoing

arXiv:2604.19618v1 Announce Type: new Abstract: Reliable pipeline inspection is critical to safe energy transportation, but is constrained by long distances, complex terrain, and risks to human inspec

agentsarxiv-cs-ro

Applications

Benign Overfitting in Adversarial Training for Vision Transformers

arXiv:2604.19724v1 Announce Type: cross Abstract: Despite the remarkable success of Vision Transformers (ViTs) across a wide range of vision tasks, recent studies have revealed that they remain vulner

applicationsarxiv-cs-ai

Beyond Indistinguishability: Measuring Extraction Risk in LLM APIs

arXiv:2604.18697v1 Announce Type: cross Abstract: Indistinguishability properties such as differential privacy bounds or low empirically measured membership inference are widely treated as proxies to

researcharxiv-cs-cl