Failure-mode index

Search what already failed

A searchable index of real negative results, null findings, and replication failures from the published literature — so you can learn what didn't work before repeating it.

All Replication Failure Negative / Null Result Report Failed Experiment Report Abandoned Hypothesis Methods Dead-End Short Note Null Dataset Protocol

WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record (title, authors, DOI) compiled from open scholarly databases, with the abstract shown in full only where the paper is openly licensed (e.g. Creative Commons); otherwise a short excerpt is shown for reference under fair use. WASTE classifies each work by failure type; classifications are automated and approximate.

By fieldMedicine 12,222 Computer Science 744 Biochemistry, Genetics and Molecular Biology 415 Social Sciences 302 Psychology 299 Physics 280 Neuroscience 244 Economics, Econometrics and Finance 196 Environmental Science 172 Mathematics 157 Agricultural and Biological Sciences 138 Engineering 135

750 results in Failed Experiment Report · page 25 of 25

Failed Experiment ReportOpen accessComputer Science

Token-Efficient RL for LLM Reasoning

Alan Lee, Harry Tong · 2025 · arXiv

We propose reinforcement learning (RL) strategies tailored for reasoning in large language models (LLMs) under strict memory and compute limits, with a particular focus on compatibility with LoRA fine-tuning. Building on early policy gradient methods with baseline subtraction, we design critic-free methods that operate on a small, informative subset of output tokens to reduce memory usage and stabilize training. We introduce S-GRPO, a stochastic variant of Group Relative Policy Optimization, and T-SPMO, a token-level prefix matching approach for fine-grained credit assignment. Applied to Qwen2

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Failed Experiment ReportOpen accessComputer Science

How to Fine-Tune a Reasoning Model? A Teacher-Student Cooperation Framework to Synthesize Student-Consistent SFT Data

Zixian Huang, Kaichen Yang, Xu Huang et al. · 2026 · arXiv

A widely adopted strategy for model enhancement is to use synthetic data generated by a stronger model for supervised fine-tuning (SFT). However, for emerging reasoning models like Qwen3-8B, this approach often fails to improve reasoning capabilities and can even lead to a substantial drop in performance. In this work, we identify substantial stylistic divergence between teacher generated data and the distribution of student as a major factor impacting SFT. To bridge this gap, we propose a Teacher-Student Cooperation Data Synthesis framework (TESSY), which interleaves teacher and student model

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Failed Experiment ReportOpen accessComputer Science

Granularity Noise Limit in Atomic-Ensemble-Based Metrology

Chen-Rong Liu, Chuang Li, Runxia Tao et al. · 2026 · arXiv

Conventional noise analysis in atomic-ensemble sensing assumes a continuous-medium approximation, thereby treating the atomic system as a deterministic dielectric. Here, we demonstrate that this assumption breaks down due to the discrete, particulate nature of the ensemble, giving rise to an intrinsic "atomic granularity noise" (AGN) that fundamentally competes with the optical measurement noise (OMN, typically photon shot noise). By introducing a discrete-atom statistical framework, we derive a unified noise-scaling law governed by a single dimensionless resource ratio, $\mathcal{R} = \bar{N}

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Failed Experiment Report

Bereket H. Selassie and the (Failed) Promise of the Eritrean Constitution

Isaac Unah · 2026 · SSRN Electronic Journal

The paper argues that Eritrea's Constitution — ratified after a costly independence struggle and designed to establish democracy, rule of law, and human rights — has never been implemented in nearly 30 years. The failure is attributed…

View details →DOI: 10.2139/ssrn.6289978