Research / Copywriting

Alignment Whack-a-Mole

A research code repository for studying how fine-tuning can trigger verbatim recall of copyrighted books in large language models. It includes preprocessing, fine-tuning, generation, and memorization-evaluation scripts, with setup notes and example data.

Clear22/30
Useful27/30
Specific18/20
Complete19/20
Alignment Whack-a-Mole screenshot

Why it was accepted

The page clearly describes an AI research project with concrete code for preprocessing books, fine-tuning models, generating outputs, and measuring memorization. The README gives enough usage detail, supported APIs/models, and setup steps to support a useful public listing.

Weakness

The snapshot does not show the full evaluation section, license, or maintenance activity beyond a small commit history, so visitors cannot fully judge project maturity or whether the tooling works end to end.

Review status

118 days ago #613 ↑ +923

Last evaluated 118 days ago. Current rank #613. Up 923 spots in the rankings.

Score history

848276827986

Related listings

Primus AI Researcher – Free screenshot

Research / Knowledge Work

Primus is an autonomous AI researcher that hypothesizes, reads papers, writes code, runs experiments on compute, and drafts research papers. The page shows example tasks, published-paper claims, waitlist access, and positioning for ML research workflows.

Below the Fold — A New York Times X-Ray Dashboard screenshot

Research / Data Visualization

An interactive dashboard that analyzes New York Times coverage since 2000 using the NYT Archive API, with views for reporters, beats, sections, subjects, geography, obituaries, and corrections.

CAD-Bench screenshot
#302 CAD-Bench
88

Research / Knowledge Work

An open benchmark and leaderboard for AI CAD agents, with 308 prompts across 20 categories and layered scoring for geometry, engineering, manufacturability, and cognition.

Benchmarking Inference Engines on Agentic Workloads screenshot

Research / Knowledge Work

A research article from Applied Compute on how agentic, tool-using workloads differ from traditional LLM benchmarks, with production observations, workload profiles, and an open-source harness for replaying traces.