Date Understanding

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

10 shown of 10 papers with code (14 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.

• Large Language Models are Zero-Shot Reasoners
  24 May 2022 4 repositories listed Syntology ran 0 of 4 samples · 4 unverified · 1 pointer-only (licence)
  Pretrained large language models (LLMs) are widely used in many sub-fields of natural language processing (NLP) and generally known as excellent few-shot learners with task-specific exemplars.
• 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.
• BloombergGPT: A Large Language Model for Finance
  30 Mar 2023 2 repositories listed
  The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering.
• 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.
• Instance-level quantitative saliency in multiple sclerosis lesion segmentation
  13 Jun 2024 1 repository listed
  Saliency maps (based on SmoothGrad) in FLAIR showed positive values inside a lesion and negative in its neighborhood.
• Understanding the Weakness of Large Language Model Agents within a Complex Android Environment
  9 Feb 2024 1 repository listed Syntology ran 2 of 4 samples · 2 unverified · 4 pointer-only (licence)
  These challenges motivate AndroidArena, an environment and benchmark designed to evaluate LLM agents on a modern operating system.
• ReGAL: Refactoring Programs to Discover Generalizable Abstractions
  29 Jan 2024 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  While large language models (LLMs) are increasingly being used for program synthesis, they lack the global view needed to develop useful abstractions; they generally predict programs one at a time, often repeating the…
• EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning
  16 Sep 2023 1 repository listed
  On average, EchoPrompt improves the Zero-shot-CoT performance of code-davinci-002 by 5% in numerical tasks and 13% in reading comprehension tasks.
• Dataset and Baseline System for Multi-lingual Extraction and Normalization of Temporal and Numerical Expressions
  31 Mar 2023 1 repository listed
  Temporal and numerical expression understanding is of great importance in many downstream Natural Language Processing (NLP) and Information Retrieval (IR) tasks.
• Japanese Beauty Marketing on Social Media: Critical Discourse Analysis Meets NLP
  1 Dec 2021 1 repository listed
  This project is a pilot study intending to combine traditional corpus linguistics, Natural Language Processing, critical discourse analysis, and digital humanities to gain an up-to-date understanding of how beauty is…

Syntology lines on 4 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.