QQP

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

2 datasets 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.

Most implemented papers archive 2025-07-28

12 shown of 12 papers with code (34 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.

• GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
  20 Apr 2018 11 repositories listed Syntology ran 5 of 14 samples · 9 unverified · 1 pointer-only (licence)
  For natural language understanding (NLU) technology to be maximally useful, both practically and as a scientific object of study, it must be general: it must be able to process language in a way that is not exclusively…
• From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression
  14 Dec 2021 2 repositories listed
  Unified in contrastive learning, CAP enables the pruned model to learn from the pre-trained model for task-agnostic knowledge, and fine-tuned model for task-specific knowledge.
• TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings
  29 Feb 2024 1 repository listed
  This paper presents the Text Encoding Diffusion Model (TEncDM), a novel approach to diffusion modeling that operates in the space of pre-trained language model encodings.
• BatchPrompt: Accomplish more with less
  1 Sep 2023 1 repository listed
  We have two initial observations for prompting with batched data.
• Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning
  21 May 2023 1 repository listed
  Combining large language models with logical reasoning enhances their capacity to address problems in a robust and reliable manner.
• Enhancing Text Generation with Cooperative Training
  16 Mar 2023 1 repository listed
  Recently, there has been a surge in the use of generated data to enhance the performance of downstream models, largely due to the advancements in pre-trained language models.
• AGRO: Adversarial Discovery of Error-prone groups for Robust Optimization
  2 Dec 2022 1 repository listed Syntology ran 3 of 12 samples · 9 unverified · 12 pointer-only (licence)
  We propose AGRO -- Adversarial Group discovery for Distributionally Robust Optimization -- an end-to-end approach that jointly identifies error-prone groups and improves accuracy on them.
• Linear Connectivity Reveals Generalization Strategies
  24 May 2022 1 repository listed
  It is widely accepted in the mode connectivity literature that when two neural networks are trained similarly on the same data, they are connected by a path through parameter space over which test set accuracy is…
• Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation
  3 Sep 2021 1 repository listed
  Exemplar-Guided Paraphrase Generation (EGPG) aims to generate a target sentence which conforms to the style of the given exemplar while encapsulating the content information of the source sentence.
• LEAP: Learnable Pruning for Transformer-based Models
  30 May 2021 1 repository listed Syntology ran 2 of 2 samples · 0 unverified
  Moreover, in order to reduce hyperparameter tuning, a novel adaptive regularization coefficient is deployed to control the regularization penalty adaptively.
• Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level
  13 May 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  We develop statistically rigorous methods to address this, and after accounting for pretraining and finetuning noise, we find that our BERT-Large is worse than BERT-Mini on at least 1-4% of instances across MNLI, SST-2,…
• On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks
  10 Oct 2020 1 repository listed
  Many pairwise classification tasks, such as paraphrase detection and open-domain question answering, naturally have extreme label imbalance (e.

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.