Empirical forensic study of OpenClaw recovers interaction traces, proposes an agent artifact taxonomy, and flags nondeterminism from LLM-mediated execution as a foundational issue for digital forensics.
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Imbalanced data problem in machine learning: A review,
Canonical reference. 76% of citing Pith papers cite this work as background.
53
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76% of classified citations
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background 13
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representative citing papers
Introduces a method to design structure-specific relational inductive biases for a base transformer architecture, enabling end-to-end transcription of documents with intrinsic structures, demonstrated on sheet music, shape drawings, and mechanical engineering drawings.
A 14-code content model for local post-hoc AI explanations, derived from 325 user statements and validated by experts with high reliability scores.
Researchers derived 19 design guidelines for AI-supported adult learning from thematic analysis of real deployments and demonstrated their use via heuristic evaluation and an ideation tool.
EOS-Bench creates thousands of satellite scheduling test cases spanning small to large scales and evaluates multiple solver types across five performance metrics.
CF-VLA uses a coarse initialization over endpoint velocity followed by single-step refinement to achieve strong performance with low inference steps on CALVIN, LIBERO, and real-robot tasks.
InfiniLoRA decouples LoRA execution from base-model inference and reports 3.05x higher request throughput plus 54% more adapters meeting strict latency SLOs.
The first systematic review of routine computing synthesizes literature into a taxonomy of temporal, behavioral, cognitive, and variability aspects, outlining applications in health, accessibility, and adaptive support along with persistent challenges.
A Generative Flow Network framework with experience replay, exploratory policy, and physics masking samples ray paths for radio propagation up to 100x faster than exhaustive search on idealized scenarios.
FFM finds optimal fused mappings for tensor accelerators over 10,000 times faster than prior mappers while cutting energy-delay product by up to 1.8x versus hand-tuned designs.
M-ASPM decouples receiver sensitivity gains from collision exposure in LPWANs via a single shared detection channel that handles synchronization, CFO estimation, and payload channel selection across multiple payload channels.
Proposes data-aware static analysis combining data/control flow and API contracts to detect semantic faults in ML code early, shown on sample real-world notebooks.
dille detects silent semantic faults in random forest ML pipelines with 91% precision via data-informed static analysis on Kaggle notebooks, finding 12-18% of scripts affected.
VISOR is a VLM-based automated test oracle that evaluates robot task correctness and quality from videos while reporting its own uncertainty, tested on GPT and Gemini across four tasks and over 1000 videos with Gemini showing higher recall and GPT higher precision but low uncertainty-correctness tie
MooD introduces continuous valence-arousal modeling with VA-aware retrieval and perception-enhanced guidance for efficient, controllable affective image editing, plus a new AffectSet dataset.
Lottery BP adds randomness to belief propagation decoding and uses syndrome voting to achieve far higher accuracy on topological quantum codes while reducing reliance on expensive global decoders.
KAIROS reduces power by 27% on average (up to 39.8%) for agentic AI inference by using long-lived context to jointly manage GPU frequency, concurrency, and request routing across instances.
A co-design framework using approximate matrix decomposition and genetic algorithms delivers 33% average latency reduction in TinyML CNN FPGA accelerators with 1.3% average accuracy loss versus standard systolic arrays.
ANVIL automates analogy-based instructional animations for computer science by chaining LLM analogy generation, screenplay structuring, manim code production with repair, and mixed human-automated evaluations.
DynamicsLLM uses LLMs to generate execution traces that cover three times more code smell-related events than the prior Dynamics tool on 333 F-Droid Android apps, with a hybrid method adding 25.9% coverage for low-activity apps.
Case study of 18,020 Kubernetes PRs shows label-diff congruence is prevalent and stable, with higher congruence linked to fewer review participants among core developers and more among one-time contributors.
Agentic Business Process Management reframes BPM around autonomous agents that must exhibit framed autonomy, explainability, conversational actionability, and self-modification to keep their actions aligned with organizational objectives.
CoGate-LSTM adds prototype-guided cosine feature-space gating to a character-level BiLSTM with multi-source embeddings and focal loss, reaching 0.881 macro-F1 on Jigsaw toxic comments while using 7.3M parameters and outperforming fine-tuned BERT by 6.9 points on minority labels.
Empirical analysis of 338 PRs with self-admitted ChatGPT usage shows low full integration (median 25%), selective adaptation patterns, and broader influence on developer reasoning during reviews.
citing papers explorer
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Foundations for Agentic AI Investigations from the Forensic Analysis of OpenClaw
Empirical forensic study of OpenClaw recovers interaction traces, proposes an agent artifact taxonomy, and flags nondeterminism from LLM-mediated execution as a foundational issue for digital forensics.
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A document is worth a structured record: Principled inductive bias design for document recognition
Introduces a method to design structure-specific relational inductive biases for a base transformer architecture, enabling end-to-end transcription of documents with intrinsic structures, demonstrated on sheet music, shape drawings, and mechanical engineering drawings.
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What Should Explanations Contain? A Human-Centered Explanation Content Model for Local, Post-Hoc Explanations
A 14-code content model for local post-hoc AI explanations, derived from 325 user statements and validated by experts with high reliability scores.
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Guidelines for Designing AI Technologies to Support Adult Learning
Researchers derived 19 design guidelines for AI-supported adult learning from thematic analysis of real deployments and demonstrated their use via heuristic evaluation and an ideation tool.
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EOS-Bench: A Comprehensive Benchmark for Earth Observation Satellite Scheduling
EOS-Bench creates thousands of satellite scheduling test cases spanning small to large scales and evaluates multiple solver types across five performance metrics.
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CF-VLA: Efficient Coarse-to-Fine Action Generation for Vision-Language-Action Policies
CF-VLA uses a coarse initialization over endpoint velocity followed by single-step refinement to achieve strong performance with low inference steps on CALVIN, LIBERO, and real-robot tasks.
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InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models
InfiniLoRA decouples LoRA execution from base-model inference and reports 3.05x higher request throughput plus 54% more adapters meeting strict latency SLOs.
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Routine Computing: A Systematic Review of Sensing Daily Life Dimensions Towards Human-Centered Goals
The first systematic review of routine computing synthesizes literature into a taxonomy of temporal, behavioral, cognitive, and variability aspects, outlining applications in health, accessibility, and adaptive support along with persistent challenges.
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Transform-Invariant Generative Ray Path Sampling for Efficient Radio Propagation Modeling
A Generative Flow Network framework with experience replay, exploratory policy, and physics masking samples ray paths for radio propagation up to 100x faster than exhaustive search on idealized scenarios.
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Fast and Fusiest: An Optimal Fusion-Aware Mapper for Accelerator Design
FFM finds optimal fused mappings for tensor accelerators over 10,000 times faster than prior mappers while cutting energy-delay product by up to 1.8x versus hand-tuned designs.
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Collision-resistant multi-channel M-ASPM configurations with shared single detection channel
M-ASPM decouples receiver sensitivity gains from collision exposure in LPWANs via a single shared detection channel that handles synchronization, CFO estimation, and payload channel selection across multiple payload channels.
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Data-aware Static Analysis: Improving Detection of Semantic Faults in Machine Learning Code Using Data Characteristics
Proposes data-aware static analysis combining data/control flow and API contracts to detect semantic faults in ML code early, shown on sample real-world notebooks.
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Are We Lost in the Woods? Detecting Silent Semantic Faults for Random Forest Classifiers with Data-informed Static Analysis
dille detects silent semantic faults in random forest ML pipelines with 91% precision via data-informed static analysis on Kaggle notebooks, finding 12-18% of scripts affected.
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VISOR: A Vision-Language Model-based Test Oracle for Testing Robots
VISOR is a VLM-based automated test oracle that evaluates robot task correctness and quality from videos while reporting its own uncertainty, tested on GPT and Gemini across four tasks and over 1000 videos with Gemini showing higher recall and GPT higher precision but low uncertainty-correctness tie
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MooD: Perception-Enhanced Efficient Affective Image Editing via Continuous Valence-Arousal Modeling
MooD introduces continuous valence-arousal modeling with VA-aware retrieval and perception-enhanced guidance for efficient, controllable affective image editing, plus a new AffectSet dataset.
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Lottery BP: Unlocking Quantum Error Decoding at Scale
Lottery BP adds randomness to belief propagation decoding and uses syndrome voting to achieve far higher accuracy on topological quantum codes while reducing reliance on expensive global decoders.
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KAIROS: Stateful, Context-Aware Power-Efficient Agentic Inference Serving
KAIROS reduces power by 27% on average (up to 39.8%) for agentic AI inference by using long-lived context to jointly manage GPU frequency, concurrency, and request routing across instances.
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Co-Design of CNN Accelerators for TinyML using Approximate Matrix Decomposition
A co-design framework using approximate matrix decomposition and genetic algorithms delivers 33% average latency reduction in TinyML CNN FPGA accelerators with 1.3% average accuracy loss versus standard systolic arrays.
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ANVIL: Analogies and Videos for Lecturers
ANVIL automates analogy-based instructional animations for computer science by chaining LLM analogy generation, screenplay structuring, manim code production with repair, and mixed human-automated evaluations.
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DynamicsLLM: a Dynamic Analysis-based Tool for Generating Intelligent Execution Traces Using LLMs to Detect Android Behavioural Code Smells
DynamicsLLM uses LLMs to generate execution traces that cover three times more code smell-related events than the prior Dynamics tool on 333 F-Droid Android apps, with a hybrid method adding 25.9% coverage for low-activity apps.
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Efficiency for Experts, Visibility for Newcomers: A Case Study of Label-Code Alignment in Kubernetes
Case study of 18,020 Kubernetes PRs shows label-diff congruence is prevalent and stable, with higher congruence linked to fewer review participants among core developers and more among one-time contributors.
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Agentic Business Process Management: A Research Manifesto
Agentic Business Process Management reframes BPM around autonomous agents that must exhibit framed autonomy, explainability, conversational actionability, and self-modification to keep their actions aligned with organizational objectives.
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CoGate-LSTM: Prototype-Guided Feature-Space Gating for Mitigating Gradient Dilution in Imbalanced Toxic Comment Classification
CoGate-LSTM adds prototype-guided cosine feature-space gating to a character-level BiLSTM with multi-source embeddings and focal loss, reaching 0.881 macro-F1 on Jigsaw toxic comments while using 7.3M parameters and outperforming fine-tuned BERT by 6.9 points on minority labels.
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PatchTrack: A Comprehensive Analysis of ChatGPT's Influence on Pull Request Outcomes
Empirical analysis of 338 PRs with self-admitted ChatGPT usage shows low full integration (median 25%), selective adaptation patterns, and broader influence on developer reasoning during reviews.
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Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy
OmniAct framework integrates planning, memory, and verification to enable persistent autonomy in omnimodal embodied agents, showing improved success and stable context in 40 real-world tasks.
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FetSelect: Task-Specific Architectures and Self-Supervised Learning for Automated Fetal Ultrasound Frame Selection
FetSelect pairs a frozen vision foundation model with a hybrid multi-head design and BYOL pretraining on ultrasound data to select quality fetal frames, reporting mean AUROC 0.956 on expert-labeled test data.
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Forecasting what Matters: Decision-Focused RL for Controlled EV Charging with Unknown Departure Times
Decision-focused RL framework trains forecaster end-to-end with RL agent for EV charging under unknown departure times, yielding up to 14% higher reward and 55% less unsupplied energy than separate training.
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Multidimensional Resilience for Electrical Power Systems: Systematic Review, Integrated Index, and Validation under Real-World Cyber-Physical Attack Scenarios
A new Multidimensional Resilience Index shows that simultaneous failures across physical, cyber, and exogenous dimensions produce 46-fold greater resilience loss in power systems than isolated stress.
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eDySec: A Deep Learning-based Explainable Dynamic Analysis Framework for Detecting Malicious Packages in PyPI Ecosystem
eDySec is a deep learning-based framework that detects malicious PyPI packages through dynamic analysis, halving feature dimensionality, reducing false positives by 82%, false negatives by 79%, and boosting accuracy by 3% with near-perfect stability.
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Autark: A Serverless Toolkit for Prototyping Urban Visual Analytics Systems
Autark is a serverless toolkit that enables rapid prototyping of urban visual analytics systems via domain-aware abstractions and supports more reliable LLM-assisted coding.
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Cross-Validated Cross-Channel Self-Attention and Denoising for Automatic Modulation Classification
A new AMC architecture with cross-channel self-attention and feature-preserving denoising achieves 3-14% higher accuracy than benchmarks at low-to-medium SNRs on the RML2018.01a dataset.
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SafeScreen: A Safety-First Screening Framework for Personalized Video Retrieval for Vulnerable Users
SafeScreen enforces individualized safety constraints as a prerequisite for video retrieval by using profile extraction, adaptive VideoRAG analysis, and LLM decision-making to approve content for vulnerable users.
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RAG-DIVE: A Dynamic Approach for Multi-Turn Dialogue Evaluation in Retrieval-Augmented Generation
RAG-DIVE uses an LLM to dynamically generate, validate, and evaluate multi-turn dialogues for assessing RAG system performance in interactive settings.
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DoSReMC: Domain Shift Resilient Mammography Classification using Batch Normalization Adaptation
DoSReMC improves cross-domain generalization in mammography classification by fine-tuning only batch normalization and fully connected layers of pretrained CNNs while preserving convolutional filters, combined with adversarial training.
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Physics-Informed Graph Neural Networks for Transverse Momentum Estimation in CMS Trigger Systems
Physics-informed GNNs with four detector-aware graph constructions and a custom message passing layer achieve MAE 0.8525 for pT estimation on CMS trigger data with over 55% fewer parameters than baselines.
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Ageing-aware Energy Management for Residential Multi-Carrier Energy Systems
Develops an ageing-aware nonlinear economic MPC for multi-carrier residential energy systems using physics-based battery models, reporting 10% grid cost reduction and 20% less degradation with LFP vs NMC cells plus 10%/5% gains over state-of-the-art in summer conditions.
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Multi-Head Attention-Based Feature Extractor Integration with Soft Actor-Critic for Porosity Prediction and Process Parameter Optimization in Additive Manufacturing
Integrates multi-head attention with SAC for faster convergence in optimizing additive manufacturing parameters to minimize porosity, outperforming DQN, PPO, TD3, and vanilla SAC.
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Technological Fitness and Regional Growth in Japan
Regional fitness from bipartite patent networks positively predicts subsequent GRP per capita growth in Japanese prefectures using fixed-effects panel models, with heterogeneity by initial income.
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Benchmarking Mythos-Linked Bug Rediscovery
A benchmarking experiment finds low rediscovery rates for three models on six Mythos-linked bug tasks, with only six target matches across 54 attempts under controlled prompting.
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Analysis of wireless network access logs for a hierarchical characterization of user mobility
Hierarchical clustering of Wi-Fi access points yields user mobility models with transition matrices and time vectors that show lower complexity than flat campus-wide models on real connection logs.
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Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges
A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.
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Autonomous Unmanned Aircraft Systems for Enhanced Search and Rescue of Drowning Swimmers: Image-Based Localization and Mission Simulation
A UAS with YOLO-based swimmer detection and DES simulations reduces drowning rescue response time by a factor of five versus standard operations in tested lake areas.
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Vision-Based Risk Aware Emergency Landing for UAVs in Complex Urban Environments
A vision-based system uses deep neural networks for pixel-level risk assessment and risk-map algorithms to identify stable safe landing zones for UAV emergency descents in dynamic urban settings.
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Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directions
A survey of trajectory prediction techniques for autonomous vehicles that proposes a taxonomy, overviews the prediction pipeline, and highlights remaining research gaps.
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Attentive Dilated Convolution for Automatic Sleep Staging using Force-directed Layout
AttDiCNN reaches 98.56%, 99.66%, and 99.08% accuracy on EDFX, HMC, and NCH sleep datasets via force-directed visibility graph EEG representations and a three-module attentive dilated CNN architecture.
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Zero-shot Transfer of Reinforcement Learning Control Policies for the Swing-Up and Stabilization of a Cart-Pole System
Zero-shot sim-to-real transfer of independently trained RL policies for cart-pole swing-up and stabilization is achieved via sensitivity-guided domain randomization, linear curriculum learning, and first-order action smoothing with Simulink switching logic.
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Intelligent Character Recognition of Handwritten Forms with Deep Neural Networks
Single deep neural network trained on synthetic EMNIST-derived data performs joint detection and classification of handwritten Latin letters and reaches 88.28 percent on real exam forms.
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Software Engineering for Self-Adaptive Robotics: A Research Agenda
This paper proposes a research agenda for software engineering of self-adaptive robotic systems along lifecycle stages and enabling technologies, identifying challenges and a roadmap to 2030.
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Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation
A literature survey that organizes prompting, fine-tuning, preference optimization, and context-aware techniques for LLM-based machine translation with emphasis on low-resource languages.
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Simulation of entanglement based quantum networks for performance characterization
NetSquid simulations characterize how memory quality, noise, distances, switches, purification and error correction affect end-to-end fidelity in entanglement-based quantum networks and yield design guidelines.