ListOps

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

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.

Most implemented papers archive 2025-07-28

17 shown of 17 papers with code (22 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.

• Efficiently Modeling Long Sequences with Structured State Spaces
  31 Oct 2021 8 repositories listed Syntology ran 28 of 55 samples · 27 unverified · 3 pointer-only (licence)
  A central goal of sequence modeling is designing a single principled model that can address sequence data across a range of modalities and tasks, particularly on long-range dependencies.
• Mega: Moving Average Equipped Gated Attention
  21 Sep 2022 7 repositories listed Syntology ran 12 of 13 samples · 1 unverified · 8 pointer-only (licence)
  The design choices in the Transformer attention mechanism, including weak inductive bias and quadratic computational complexity, have limited its application for modeling long sequences.
• Simplified State Space Layers for Sequence Modeling
  9 Aug 2022 6 repositories listed Syntology ran 4 of 19 samples · 15 unverified · 3 pointer-only (licence)
  Models using structured state space sequence (S4) layers have achieved state-of-the-art performance on long-range sequence modeling tasks.
• Going Beyond Linear Transformers with Recurrent Fast Weight Programmers
  11 Jun 2021 5 repositories listed Syntology ran 5 of 12 samples · 7 unverified
  Transformers with linearised attention (''linear Transformers'') have demonstrated the practical scalability and effectiveness of outer product-based Fast Weight Programmers (FWPs) from the '90s.
• Long Range Arena: A Benchmark for Efficient Transformers
  8 Nov 2020 5 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  In the recent months, a wide spectrum of efficient, fast Transformers have been proposed to tackle this problem, more often than not claiming superior or comparable model quality to vanilla Transformer models.
• ListOps: A Diagnostic Dataset for Latent Tree Learning
  17 Apr 2018 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  In this paper we introduce ListOps, a toy dataset created to study the parsing ability of latent tree models.
• Investigating Recurrent Transformers with Dynamic Halt
  1 Feb 2024 1 repository listed
  In this paper, we comprehensively study the inductive biases of two major approaches to augmenting Transformers with a recurrent mechanism: (1) the approach of incorporating a depth-wise recurrence similar to Universal…
• Cached Transformers: Improving Transformers with Differentiable Memory Cache
  20 Dec 2023 1 repository listed
  This work introduces a new Transformer model called Cached Transformer, which uses Gated Recurrent Cached (GRC) attention to extend the self-attention mechanism with a differentiable memory cache of tokens.
• Opening the Black Box: Analyzing Attention Weights and Hidden States in Pre-trained Language Models for Non-language Tasks
  21 Jun 2023 1 repository listed
  Investigating deep learning language models has always been a significant research area due to the ``black box" nature of most advanced models.
• Beam Tree Recursive Cells
  31 May 2023 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  We propose Beam Tree Recursive Cell (BT-Cell) - a backpropagation-friendly framework to extend Recursive Neural Networks (RvNNs) with beam search for latent structure induction.
• Sequence Modeling with Multiresolution Convolutional Memory
  2 May 2023 1 repository listed Syntology ran 3 of 8 samples · 5 unverified
  Popular approaches in the space tradeoff between the memory burden of brute-force enumeration and comparison, as in transformers, the computational burden of complicated sequential dependencies, as in recurrent neural…
• Training Discrete Deep Generative Models via Gapped Straight-Through Estimator
  15 Jun 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  While deep generative models have succeeded in image processing, natural language processing, and reinforcement learning, training that involves discrete random variables remains challenging due to the high variance of…
• Dynamic Token Normalization Improves Vision Transformers
  5 Dec 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  It is difficult for Transformers to capture inductive bias such as the positional context in an image with LN.
• ORCHARD: A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical Reasoning
  28 Nov 2021 1 repository listed
  The ability to reason with multiple hierarchical structures is an attractive and desirable property of sequential inductive biases for natural language processing.
• The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization
  14 Oct 2021 1 repository listed Syntology ran 7 of 11 samples · 4 unverified
  Despite progress across a broad range of applications, Transformers have limited success in systematic generalization.
• Modeling Hierarchical Structures with Continuous Recursive Neural Networks
  10 Jun 2021 1 repository listed Syntology ran 1 of 4 samples · 3 unverified
  We also show that CRvNN performs comparably or better than prior latent structure models on real-world tasks such as sentiment analysis and natural language inference.
• Ordered Memory
  29 Oct 2019 1 repository listed Syntology ran 0 of 8 samples · 8 unverified
  Inspired by Ordered Neurons (Shen et al., 2018), we introduce a new attention-based mechanism and use its cumulative probability to control the writing and erasing operation of the memory.

Syntology lines on 13 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.