dsgym-a-holistic-framework-for-evaluating-and-trai

name	dsgym-a-holistic-framework-for-evaluating-and-trai
title	DSGym: A Holistic Framework for Evaluating and Training Data Science Agents
version	0.0.2
engine	skillxiv-v0.0.2-claude-opus-4.6
license	MIT
url	https://arxiv.org/abs/2601.16344
keywords	["agent","training","benchmark","framework"]
description	Implement techniques from DSGym: A Holistic Framework for Evaluating and Training Data Science Agents. Data science agents promise to accelerate discovery and insight-generation by turning data into executable analyses and findings

Overview

This skill implements concepts from the research paper [2601.16344].

When to Use

• When you need to implement techniques described in this paper
• When working on problems that this research addresses
• When you want to understand the core concepts and methodology

When NOT to Use

• This skill provides research-level insights; production implementations may require additional engineering
• Some concepts may require significant tuning for specific use cases
• Always evaluate applicability to your specific problem domain

Key Concepts

The paper addresses: Data science agents promise to accelerate discovery and insight-generation by turning data into executable analyses and findings. Yet existing data science benchmarks fall short due to fragmented evaluation interfaces that make cross-benchmark comparison difficult, narrow task coverage and a lack of...

For detailed methodology and implementation details, refer to the full paper.