Human-in-the-Loop Without Killing Throughput
How we stopped reviewing every agent action and started routing human attention where it actually mattered The post Human-in-the-Loop Without Killing Throughput appeared first on Towards Data Science.
Daily edition · AI Research
The daily ledger
TILens turns technical updates into a focused daily brief: official releases, trusted reporting, and practitioner analysis, deduplicated and organized by topic.
From One Agent to a Team: Understanding Codex Subagents
A hands-on guide to defining specialist agents and coordinating their work in the Codex CLI The post From One Agent to a Team: Understanding Codex Subagents appeared first on Towards Data Science.
Connecting My LangGraph AI Agent to Postgres
How to run the backend locally with Docker or in the cloud The post Connecting My LangGraph AI Agent to Postgres appeared first on Towards Data Science.
Why Claude Code Time Estimates Are Poor
Be a better communicator with LLM programming The post Why Claude Code Time Estimates Are Poor appeared first on Towards Data Science.
Graph-Based Pseudo-multimodal Contrastive Learning for 12-Lead ECG Representations
arXiv:2608.26964v1 Announce Type: new Abstract: 12-lead electrocardiogram (ECG) is a standard, non-invasive examination widely used for diagnosing coronary artery disease, where clinical interpretation relies on…
Aitchison Embeddings for Learning Compositional Graph Representations
arXiv:2605.00716v3 Announce Type: replace Abstract: Representation learning is central to graph machine learning, powering tasks such as link prediction and node classification. However, most graph embeddings are hard…
Bayesian methods and Markov chain Monte Carlo algorithms for curve reconstruction and point cloud data analysis
arXiv:2608.26490v1 Announce Type: new Abstract: Point-cloud data routinely captured by modern imaging and sensor technologies provide detailed geometric descriptions of objects and environments, but their analysis is…
FedCMAPSS: A Benchmark for Federated Learning in Remaining Useful Life Estimation
arXiv:2608.26433v1 Announce Type: new Abstract: Data-driven prognostics and health management has emerged as a key enabler for Industry 4.0, yet the development of robust remaining useful life (RUL) estimation models is…
Recovering Expert Critic-Sourced Network Adjacency between Musical Artists from Acoustic Distributions: A Construct-Validity Approach
arXiv:2608.27291v1 Announce Type: cross Abstract: Music recommendation relies primarily on two signals: user-item interactions, which fail in the cold-start regime, and intrinsic musical content, available for any…
Plain Transformers Can be Powerful Graph Learners
arXiv:2504.12588v4 Announce Type: replace Abstract: Transformers have attained outstanding performance across various modalities, owing to their simple but powerful scaled-dot-product (SDP) attention mechanisms.…
When Privacy Hurts Mergeability: Geometry-Aware Model Merging under Differential Privacy
arXiv:2608.26655v1 Announce Type: new Abstract: Model merging promises to construct a single multi-task model from independently fine-tuned task models without accessing the original task data. This makes it attractive…
Puro-2B: Poor Lab's Qwen2-1.5B Trained on RTX 5090 within $5090
arXiv:2608.27370v1 Announce Type: cross Abstract: Language model pretraining has become almost synonymous with prohibitive cost, placing it out of reach for much of the academic and open-source communities. Although…
hoBIT: A Profile-Aware Retrieval-Augmented Chatbot for University Academic Advising
arXiv:2608.26604v1 Announce Type: cross Abstract: In university academic advising, identical questions can require different answers depending on a student's department, admission cohort, and degree program, causing…
Classical and Hybrid Quantum Machine Learning for Trigger-Like Event Selection on CMS Open Data: An Eight-Qubit, PCA-Constrained Benchmark
arXiv:2608.26224v1 Announce Type: cross Abstract: Event triggering sits at the heart of high-energy physics, where the rare events of interest must be retained while an overwhelming background is discarded under tight…
Finding the Right Evidence: Factor-Guided Coarse-to-Fine Reasoning for Long Videos
arXiv:2608.26355v1 Announce Type: cross Abstract: While LVLMs rapidly improve, long-video question answering still remains challenging: relevant evidence is sparse, and question-relevant context often fails to provide…
Pruning Binarized Neural Networks: A Dedicated Framework and Globally Weighted Algorithms
arXiv:2608.26233v1 Announce Type: new Abstract: Extreme compression of deep neural networks, up to full binarization, dramatically reduces memory footprint and arithmetic complexity, facilitating deployment on…
Data-driven Koopman mode approximation: A neural power iteration algorithm
arXiv:2608.26943v1 Announce Type: cross Abstract: This paper proposes a novel data-driven algorithm to approximate the dominant eigenfunctions (aka.~modes) of the Koopman operator of nonlinear dynamical systems using…
Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models
arXiv:2608.27259v1 Announce Type: new Abstract: World Action Models (WAMs) augment robot policies by predicting how task-relevant scene states may evolve under interaction. Recent WAMs increasingly perform such…
Mol-JEPA: A multimodal Joint Embedding Predictive Architecture for Molecules
arXiv:2608.22642v2 Announce Type: replace Abstract: Despite recent advances in molecular foundation models, several limitations remain, such as chemically invalid augmentations, modality collapse, and incomplete…
LowRankArena: A Standardized Evaluation Platform for SVD-Based LLM Compression
arXiv:2608.26389v1 Announce Type: cross Abstract: SVD-based low-rank compression has become a fast-growing direction for reducing the memory and computational cost of large language models (LLMs). However, meaningful…
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