datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
icml-2026-reproductions
ICML 2026 Agent Reproducibility Challenge — Logbooks
A living mirror of all public reproduction logbooks from the ICML 2026 Agent Reproducibility Challenge.
Agents attempt to reproduce claims from ICML 2026 papers. Each logbook records the reproduction process, evidence, and verdict for each claim.
Structure
├── papers.json # All 6341 ICML 2026 papers (metadata)
├── logbooks.csv # Main index: one row per logbook (agent × paper ×… See the full description on the dataset page: https://huggingface.co/datasets/qy2100/icml-2026-reproductions.Innoc2Scam-bench-ICML26
Innoc2Scam-bench
Innoc2Scam-bench is a benchmark for auditing whether production LLMs transform seemingly innocuous developer prompts into code that points to malicious scam infrastructure.
This dataset was constructed for the paper "Scam2Prompt: A Scalable Framework for Auditing Malicious Scam Endpoints in Production LLMs".
Authors: Zhiyang Chen, Tara Saba, Xun Deng, Xujie Si, Fan LongContact: zhiychen@cs.toronto.eduGitHub:… See the full description on the dataset page: https://huggingface.co/datasets/jeffchen006/Innoc2Scam-bench-ICML26.full_before_conv_icmll_pub
Iterative vs Recursive Code Pairs
Coding problems sourced from LeetCode and Codeforces, each with a verified
iterative and recursive Python solution. Test cases are timed and binned
by per-problem difficulty (tc_difficulty: easy | medium | hard). Function names
in both solutions are deterministically obfuscated (*_obfuscated columns) for
benchmarks where lexical signal would leak the paradigm.
Columns
id, task_id, source, difficulty, title, description, tags, rating… See the full description on the dataset page: https://huggingface.co/datasets/CLEVDEV/full_before_conv_icmll_pub.icml_obf
Iterative vs Recursive Code Pairs — with Full AST Obfuscation
Verified iterative/recursive Python solution pairs from LeetCode and Codeforces.
Extends CLEVDEV/full_before_conv_icmll_pub with full-variable AST
obfuscation applied to every user-defined identifier.
Columns added on top of the source dataset
iterative_solution_fullobf — iterative solution with every user-defined
variable, argument, function, class, and import renamed to v{n} / f{n}
tokens. Type annotations… See the full description on the dataset page: https://huggingface.co/datasets/CLEVDEV/icml_obf.