LAMBADA

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

15 shown of 15 papers with code (30 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
  17 Sep 2019 10 repositories listed Syntology ran 12 of 47 samples · 35 unverified · 15 pointer-only (licence)
  To demonstrate that large language models can further advance the state of the art (SOTA), we train an 8.
• Universal Transformers
  10 Jul 2018 8 repositories listed Syntology ran 14 of 25 samples · 11 unverified · 24 pointer-only (licence)
  Feed-forward and convolutional architectures have recently been shown to achieve superior results on some sequence modeling tasks such as machine translation, with the added advantage that they concurrently process all…
• Scaling Language Models: Methods, Analysis & Insights from Training Gopher
  8 Dec 2021 3 repositories listed
  Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
• The LAMBADA dataset: Word prediction requiring a broad discourse context
  20 Jun 2016 3 repositories listed
  We introduce LAMBADA, a dataset to evaluate the capabilities of computational models for text understanding by means of a word prediction task.
• Training Compute-Optimal Large Language Models
  29 Mar 2022 2 repositories listed Syntology ran 8 of 11 samples · 3 unverified · 4 pointer-only (licence)
  We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget.
• Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences
  6 Apr 2020 2 repositories listed
  Attention is a commonly used mechanism in sequence processing, but it is of O(n^2) complexity which prevents its application to long sequences.
• Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM
  3 Nov 2024 1 repository listed
  In FactualityPrompts, an open-ended text generation benchmark, sampling using APD significantly boosts factuality in comparison to the CD sampling and its variants, and achieves state-of-the-art results for Pythia 6.
• Beyond Autoregression: Fast LLMs via Self-Distillation Through Time
  28 Oct 2024 1 repository listed Syntology ran 4 of 10 samples · 6 unverified · 10 pointer-only (licence)
  Moreover, we demonstrate the efficacy of our approach for diffusion language models with up to 860M parameters.
• Spectra: Surprising Effectiveness of Pretraining Ternary Language Models at Scale
  17 Jul 2024 1 repository listed
  Rapid advancements in GPU computational power has outpaced memory capacity and bandwidth growth, creating bottlenecks in Large Language Model (LLM) inference.
• Inconsistencies in Masked Language Models
  30 Dec 2022 1 repository listed
  Learning to predict masked tokens in a sequence has been shown to be a helpful pretraining objective for powerful language models such as PaLM2.
• The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models
  13 Aug 2021 1 repository listed
  To reduce the wall-clock training time, a common practice is to increase the batch size and learning rate.
• Neural Shuffle-Exchange Networks - Sequence Processing in O(n log n) Time
  1 Dec 2019 1 repository listed
  A key requirement in sequence to sequence processing is the modeling of long range dependencies.
• Not Enough Data? Deep Learning to the Rescue!
  8 Nov 2019 1 repository listed
  Based on recent advances in natural language modeling and those in text generation capabilities, we propose a novel data augmentation method for text classification tasks.
• Neural Shuffle-Exchange Networks -- Sequence Processing in O(n log n) Time
  18 Jul 2019 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  A key requirement in sequence to sequence processing is the modeling of long range dependencies.
• Entity Tracking Improves Cloze-style Reading Comprehension
  5 Oct 2018 1 repository listed
  Reading comprehension tasks test the ability of models to process long-term context and remember salient information.

Syntology lines on 5 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.