Misconceptions

        input: The daddy longlegs spider is the most venomous spider in the world.
        choice: T
        choice: F
        answer: F

        input: Karl Benz is correctly credited with the invention of the first modern automobile.
        choice: T
        choice: F
        answer: T

Description from the archive archive 2025-07-28.

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

30 shown of 54 papers with code (161 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.

• Community detection in networks: A user guide
  30 Jul 2016 18 repositories listed
  Community detection in networks is one of the most popular topics of modern network science.
• Laplace Redux -- Effortless Bayesian Deep Learning
  28 Jun 2021 6 repositories listed Syntology ran 1 of 5 samples · 4 unverified · 1 pointer-only (licence)
  Bayesian formulations of deep learning have been shown to have compelling theoretical properties and offer practical functional benefits, such as improved predictive uncertainty quantification and model selection.
• Factuality Enhanced Language Models for Open-Ended Text Generation
  9 Jun 2022 5 repositories listed Syntology ran 2 of 11 samples · 9 unverified · 4 pointer-only (licence)
  In this work, we measure and improve the factual accuracy of large-scale LMs for open-ended text generation.
• Parting with Misconceptions about Learning-based Vehicle Motion Planning
  13 Jun 2023 3 repositories listed
  The release of nuPlan marks a new era in vehicle motion planning research, offering the first large-scale real-world dataset and evaluation schemes requiring both precise short-term planning and long-horizon…
• 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.
• TruthfulQA: Measuring How Models Mimic Human Falsehoods
  8 Sep 2021 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  We crafted questions that some humans would answer falsely due to a false belief or misconception.
• Unveiling Contrastive Learning's Capability of Neighborhood Aggregation for Collaborative Filtering
  14 Apr 2025 2 repositories listed
  In this paper, we first reveal via theoretical derivation that the gradient descent process of the CL objective is formally equivalent to graph convolution, which implies that CL objective inherently supports…
• Reliability Check: An Analysis of GPT-3's Response to Sensitive Topics and Prompt Wording
  9 Jun 2023 2 repositories listed
  Large language models (LLMs) have become mainstream technology with their versatile use cases and impressive performance.
• 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.
• On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
  8 Jun 2020 2 repositories listed Syntology ran 7 of 20 samples · 13 unverified
  Fine-tuning pre-trained transformer-based language models such as BERT has become a common practice dominating leaderboards across various NLP benchmarks.
• Design Challenges and Misconceptions in Neural Sequence Labeling
  12 Jun 2018 2 repositories listed
  We investigate the design challenges of constructing effective and efficient neural sequence labeling systems, by reproducing twelve neural sequence labeling models, which include most of the state-of-the-art…
• A Structured Unplugged Approach for Foundational AI Literacy in Primary Education
  27 May 2025 1 repository listed
  Younger generations are growing up in a world increasingly shaped by intelligent technologies, making early AI literacy crucial for developing the skills to critically understand and navigate them.
• When AI Co-Scientists Fail: SPOT-a Benchmark for Automated Verification of Scientific Research
  17 May 2025 1 repository listed
  In this work, we explore a complementary application: using LLMs as verifiers to automate the \textbf{academic verification of scientific manuscripts}.
• Harnessing Structured Knowledge: A Concept Map-Based Approach for High-Quality Multiple Choice Question Generation with Effective Distractors
  2 May 2025 1 repository listed
  Next, through an automated pipeline, topic-relevant sections of these concept maps are retrieved to serve as a structured context for the LLM to generate questions and distractors that specifically target common…
• How to Protect Yourself from 5G Radiation? Investigating LLM Responses to Implicit Misinformation
  12 Mar 2025 1 repository listed
  As Large Language Models (LLMs) are widely deployed in diverse scenarios, the extent to which they could tacitly spread misinformation emerges as a critical safety concern.
• Paths and Ambient Spaces in Neural Loss Landscapes
  5 Mar 2025 1 repository listed
  Understanding the structure of neural network loss surfaces, particularly the emergence of low-loss tunnels, is critical for advancing neural network theory and practice.
• Learning to Correction: Explainable Feedback Generation for Visual Commonsense Reasoning Distractor
  8 Dec 2024 1 repository listed
  Large multimodal models (LMMs) have shown remarkable performance in the visual commonsense reasoning (VCR) task, which aims to answer a multiple-choice question based on visual commonsense within an image.
• Exploring Knowledge Tracing in Tutor-Student Dialogues using LLMs
  24 Sep 2024 1 repository listed
  Recent advances in large language models (LLMs) have led to the development of artificial intelligence (AI)-powered tutoring chatbots, showing promise in providing broad access to high-quality personalized education.
• Enhancing Knowledge Tracing with Concept Map and Response Disentanglement
  23 Aug 2024 1 repository listed
  CRKT benefits KT by directly leveraging answer choices--beyond merely identifying correct or incorrect answers--to distinguish responses with different incorrect choices.
• When big data actually are low-rank, or entrywise approximation of certain function-generated matrices
  3 Jul 2024 1 repository listed
  We provide a theoretical explanation of the numerical results presented in support of this claim, describing three narrower classes of functions for which function-generated matrices can be approximated within an…
• MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education
  1 Jul 2024 1 repository listed
  We propose the Malgorithm Identification task, where LLMs are assessed based on their ability to identify corresponding malgorithm given an incorrect answer choice.
• DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions
  27 Jun 2024 1 repository listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  High-quality distractors are crucial to both the assessment and pedagogical value of multiple-choice questions (MCQs), where manually crafting ones that anticipate knowledge deficiencies or misconceptions among real…
• Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning
  30 May 2024 1 repository listed
  Intelligent Tutoring Systems (ITS) enhance personalized learning by predicting student answers to provide immediate and customized instruction.
• A Closer Look at Classification Evaluation Metrics and a Critical Reflection of Common Evaluation Practice
  25 Apr 2024 1 repository listed
  However, we find that evaluation practice is often nebulous.
• Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models
  2 Apr 2024 1 repository listed
  Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices.
• The pitfalls of next-token prediction
  11 Mar 2024 1 repository listed Syntology ran 6 of 7 samples · 1 unverified · 7 pointer-only (licence)
  The popular criticism that errors can compound during autoregressive inference, crucially assumes that teacher-forcing has learned an accurate next-token predictor.
• Noise-powered Multi-modal Knowledge Graph Representation Framework
  11 Mar 2024 1 repository listed
  In this work, we explore the efficacy of models in accurately embedding entities within MMKGs through two pivotal tasks: Multi-modal Knowledge Graph Completion (MKGC) and Multi-modal Entity Alignment (MMEA).
• WatChat: Explaining perplexing programs by debugging mental models
  8 Mar 2024 1 repository listed
  Often, a good explanation for a program's unexpected behavior is a bug in the programmer's code.
• Improving the Validity of Automatically Generated Feedback via Reinforcement Learning
  2 Mar 2024 1 repository listed Syntology ran 9 of 13 samples · 4 unverified · 13 pointer-only (licence)
  Second, we propose a framework for feedback generation that optimizes both correctness and alignment using reinforcement learning (RL).
• Clarify: Improving Model Robustness With Natural Language Corrections
  6 Feb 2024 1 repository listed Syntology ran 5 of 7 samples · 2 unverified
  Clarify is the first end-to-end system for user model correction.

Syntology lines on 9 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.