mlsanityData to 7 Oct 2026

SemEval-2024 Task 9: BRAINTEASER: A Novel Task Defying Common Sense

arXiv 2404.16068 ↗First posted 22 Apr 2024cs.AI cs.CL cs.LGcited by 6

On the map: LLM reasoning → Prompting and chain-of-thought reasoning

Abstract (arXiv)

While vertical thinking relies on logical and commonsense reasoning, lateral thinking requires systems to defy commonsense associations and overwrite them through unconventional thinking. Lateral thinking has been shown to be challenging for current models but has received little attention. A recent benchmark, BRAINTEASER, aims to evaluate current models' lateral thinking ability in a zero-shot setting. In this paper, we split the original benchmark to also support fine-tuning setting and present SemEval Task 9: BRAIN-TEASER(S), the first task at this competition designed to test the system's reasoning and lateral thinking ability. As a popular task, BRAINTEASER(S)'s two subtasks receive 483 team submissions from 182 participants during the competition. This paper provides a fine-grained system analysis of the competition results, together with a reflection on what this means for the ability of the systems to reason laterally. We hope that the BRAINTEASER(S) subtasks and findings in this paper can stimulate future work on lateral thinking and robust reasoning by computational models.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 18 of its 57 references that are in the map. First posted on arXiv 22 Apr 2024.

Builds on

18 of 57 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024AILS-NTUA at SemEval-2024 Task 9: Cracking Brain Teasers: Transformer Models for Lateral Thinking Puzzles1 Apr
  2. 2024MasonTigers at SemEval-2024 Task 9: Solving Puzzles with an Ensemble of Chain-of-Thoughts22 Mar
  3. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Models21 Mar

Other references · 15

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  4. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  5. 2019PIQA: Reasoning about Physical Commonsense in Natural Languagecited by 2,818
  6. 2020DeBERTa: Decoding-enhanced BERT with Disentangled Attentioncited by 2,157
  7. 2018CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledgecited by 1,793
  8. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,462
  9. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,065
  10. 2022Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distributioncited by 722
  11. 2023ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMscited by 297
  12. 2020COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphscited by 254
3 more
  1. 2023Large Language Models as General Pattern Machinescited by 196
  2. 2021RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledgecited by 60
  3. 2024Abdelhak at SemEval-2024 Task 9 : Decoding Brainteasers, The Efficacy of Dedicated Models Versus ChatGPTcited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 0; 2026: 1.

6 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2023BRAINTEASER: Lateral Thinking Puzzles for Large Language Models
  2. 2024Augmenting Lateral Thinking in Language Models with Humor and Riddle Data for the BRAINTEASER Task
  3. 2023LatEval: An Interactive LLMs Evaluation Benchmark with Incomplete Information from Lateral Thinking Puzzles
  4. 2025Creativity or Brute Force? Using Brainteasers as a Window into the Problem-Solving Abilities of Large Language Models
  5. 2024Mothman at SemEval-2024 Task 9: An Iterative System for Chain-of-Thought Prompt Optimization
  6. 2024uTeBC-NLP at SemEval-2024 Task 9: Can LLMs be Lateral Thinkers?
  7. 2025Reasoning Riddles: How Explainability Reveals Cognitive Limits in Vision-Language Models
  8. 2024OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI