Data analysis, statistics, and data engineering
UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...
Analysis of AI dominance in 2025 venture capital, its effects on market valuations, and strategic considerations for investors.
Hey all, I recently built an end-to-end fraud detection project using a large banking dataset: Trained an XGBoost model Used Databricks f...
![[2602.18481] AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper introduces AlphaForgeBench, a framework for evaluating trading strategies using Large Language Models (LLMs), addressing issues...
This paper explores Smooth Gate Functions for Soft Advantage Policy Optimization, enhancing the stability of large language model trainin...
The paper presents ZUNA, a 380M-parameter masked diffusion autoencoder designed for EEG signal superresolution and channel infilling, dem...
AgentCAT is a large language model designed to extract and analyze catalytic reaction data from chemical engineering literature, addressi...
The paper introduces a Partial Soft-Matching Distance metric for neural representational comparison, enhancing robustness against noise a...
The paper introduces CTS-Bench, a benchmark suite for evaluating graph coarsening trade-offs in Graph Neural Networks (GNNs) for Clock Tr...
BioLM-Score introduces a novel protein-ligand scoring model that enhances efficiency and interpretability in drug design by integrating g...
The paper introduces AdsorbFlow, a deterministic generative model that enhances the efficiency of adsorbate placement on catalytic surfac...
This article evaluates SAP's RPT-1 model for enterprise business process prediction, comparing its performance against traditional machin...
This article presents X-ANFIS, a novel optimization scheme for explainable neuro-fuzzy systems that balances accuracy and explainability ...
This article explores the concept of empirical unlearning in machine learning, focusing on how knowledge can persist in models even after...
This article presents DynaMO, a novel framework for optimizing reinforcement learning with verifiable rewards, addressing key challenges ...
This article evaluates the reliability of persona-conditioned large language models (LLMs) as synthetic survey respondents, revealing tha...
The paper presents HybridFL, a federated learning approach designed for financial crime detection, which integrates horizontal and vertic...
The paper introduces Virtual Parameter Sharpening (VPS), a novel technique for enhancing inference-time reasoning in transformer models t...
The article presents a novel evaluation framework for mechanistic interpretability research, utilizing AI agents to enhance research rigo...
This article examines the impact of AI-generated search summaries on website traffic, specifically analyzing how Google's AI Overviews af...
The paper presents TICL, a novel method for causal structure learning from interventional data, enhancing generalization across diverse s...
The paper presents an LLM-based system designed to replicate statistical analyses in quantitative social science, addressing the replicat...
This article discusses the development of a Multi-Agent System (MAS) that automates the generation of science assessments aligned with th...
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