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[Submitted on 25 May 2025 (v1), last revised 27 Oct 2025 (this version, v2)] View a PDF of the paper titled MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search, by Zonglin Yang and 9 other authors View PDF HTML (experimental) Abstract:Large language models (LLMs) have shown promise in automating scientific hypothesis generation, yet existing approaches primarily …

A previous article provided a of conceptual frameworks – analytical structures for representing abstract concepts and organizing data. Data scientists use such frameworks in a wide variety of contexts, from use case ideation and validation of machine learning models to productization and operation of user-facing solutions. The framework type (e.g., hierarchy, matrix, process flow, relational map) and framework dimensions (e.g., …

The countdown is almost over — tomorrow’s the day! In less than 24 hours, TechCrunch Disrupt 2025 takes over Moscone West. From October 27–29, 10,000 founders, investors, and innovators will flood San Francisco for three days of building, connecting, and deal-making. We’re just days away from live demos of never-before-seen tech and high-stakes pitches as startups compete for the $100,000 …

Most data that relates to a measurable process in the real world has a geospatial aspect to it. Organisations that manage assets over a wide geographical area, or have a business process which requires them to consider many layers of geographical attributes that require mapping, will have more complicated geospatial analytics requirements, when they start to use this data to …

With TechCrunch Disrupt 2025 in less than 3 days, we’re loading up Moscone West with 200+ can’t-miss sessions — including breakout sessions led by top leaders across the tech and startup ecosystem. Breakout sessions are tailored for hands-on learning and tactical takeaways. These first-come, first-served rooms put you shoulder-to-shoulder with operators, founders, and investors building what’s next. Don’t miss your …

[Submitted on 19 Jun 2025 (v1), last revised 22 Oct 2025 (this version, v2)] View a PDF of the paper titled Improved Exploration in GFlownets via Enhanced Epistemic Neural Networks, by Sajan Muhammad and 1 other authors View PDF Abstract:Efficiently identifying the right trajectories for training remains an open problem in GFlowNets. To address this, it is essential to prioritize …

[Submitted on 8 Jun 2025 (v1), last revised 21 Oct 2025 (this version, v2)] View a PDF of the paper titled ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition, by Daolang Huang and 4 other authors View PDF HTML (experimental) Abstract:Many critical applications, from autonomous scientific discovery to personalized medicine, demand systems that can both strategically acquire the …

Presented by Apptio, an IBM company When a technology with revolutionary potential comes on the scene, it’s easy for companies to let enthusiasm outpace fiscal discipline. Bean counting can seem short-sighted in the face of exciting opportunities for business transformation and competitive dominance. But money is always an object. And when the tech is AI, those beans can add up …

[Submitted on 13 Oct 2025 (v1), last revised 17 Oct 2025 (this version, v2)] View a PDF of the paper titled Deep Edge Filter: Return of the Human-Crafted Layer in Deep Learning, by Dongkwan Lee and 2 other authors View PDF Abstract:We introduce the Deep Edge Filter, a novel approach that applies high-pass filtering to deep neural network features to …

Vector databases (DBs), once specialist research instruments, have become widely used infrastructure in just a few years. They power today's semantic search, recommendation engines, anti-fraud measures and gen AI applications across industries. There are a deluge of options: PostgreSQL with pgvector, MySQL HeatWave, DuckDB VSS, SQLite VSS, Pinecone, Weaviate, Milvus and several others. The riches of choices sound like a …