mlsanityData to 7 Oct 2026

AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension

arXiv 2203.08992 ↗First posted 16 Mar 2022cs.CL cs.AI cs.NEcited by 8

On the map: LLM reasoning → Knowledge- and tool-augmented reasoning

Abstract (arXiv)

Recent machine reading comprehension datasets such as ReClor and LogiQA require performing logical reasoning over text. Conventional neural models are insufficient for logical reasoning, while symbolic reasoners cannot directly apply to text. To meet the challenge, we present a neural-symbolic approach which, to predict an answer, passes messages over a graph representing logical relations between text units. It incorporates an adaptive logic graph network (AdaLoGN) which adaptively infers logical relations to extend the graph and, essentially, realizes mutual and iterative reinforcement between neural and symbolic reasoning. We also implement a novel subgraph-to-node message passing mechanism to enhance context-option interaction for answering multiple-choice questions. Our approach shows promising results on ReClor and LogiQA.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 34 of its 47 references that are in the map. First posted on arXiv 16 Mar 2022.

Builds on

34 of 47 references.

References · 34

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22 more
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  2. 2020Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learningcited by 216
  3. 2020ReClor: A Reading Comprehension Dataset Requiring Logical Reasoningcited by 211
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  17. 2021DAGN: Discourse-Aware Graph Network for Logical Reasoningcited by 28
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 3; 2024: 0; 2025: 1; 2026: 1.

8 papers.

  1. 2022Reasoning with Language Model Prompting: A Surveycited by 251
  2. 2023Interpretable Multimodal Misinformation Detection with Logic Reasoningcited by 16
  3. 2022Clues Before Answers: Generation-Enhanced Multiple-Choice QAcited by 9
  4. 2022APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoningcited by 5
  5. 2023IDOL: Indicator-oriented Logic Pre-training for Logical Reasoningcited by 3
  6. 2023Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-shot Logical Reasoning over Textcited by 2
  7. 2025LogiNumSynth: Synthesizing Joint Logical-Numerical Reasoning Problems for Language Modelscited by 2
  8. 2026When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Robotic Decision-Makingcited by 2

Similar, not cited

Close in wording, no citation either way

  1. 2022Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning
  2. 2023Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension
  3. 2022Discourse-Aware Graph Networks for Textual Logical Reasoning
  4. 2022Neural Methods for Logical Reasoning Over Knowledge Graphs
  5. 2025GraphMind: Theorem Selection and Conclusion Generation Framework with Dynamic GNN for LLM Reasoning
  6. 2025Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning
  7. 2025Adaptive Graph of Thoughts: Test-Time Adaptive Reasoning Unifying Chain, Tree, and Graph Structures
  8. 2023ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph