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.
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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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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.