Who cites «Solving General Arithmetic Word Problems»

313 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
CHOIR: Harmonizing Structured Persona Diversity for Robust Collaborative LLM Reasoning — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
EvoHyper: Evolving Hypergraph Topologies for Unified Collaboration in Multi-Agent Communication — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
G-LoRA: Global-Local Decoupled Low-Rank Adaptation — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
GCoT-Decoding: Unlocking Deep Reasoning Paths for Universal Question Answering — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
Metacognitive Self-Correction for Multi-Agent System via Prototype-Guided Next-Execution Reconstruction — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
TARE: Lightweight Token-Aware Representation Editing for Fine-tuning Transformer-like Models — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
TopoDIM: One-shot Topology Generation of Diverse Interaction Modes for Multi-Agent Systems — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
A Survey on Feedback-based Multi-step Reasoning for Large Language Models on Mathematics — 2025 · arXiv:2502.14333
A Systematic Survey of Automatic Prompt Optimization Techniques — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Advancing Collaborative Debates with Role Differentiation through Multi-Agent Reinforcement Learning — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
AgentDropout: Dynamic Agent Elimination for Token-Efficient and High-Performance LLM-Based Multi-Agent Collaboration — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
AnyMAC: Cascading Flexible Multi-Agent Collaboration via Next-Agent Prediction — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
ArithmAttack: Evaluating Robustness of LLMs to Noisy Context in Math Problem Solving — 2025 · arXiv:2501.08203
Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
BanglaMATH : A Bangla benchmark dataset for testing LLM mathematical reasoning at grades 6, 7, and 8 — 2025 · Proceedings of The 3rd Workshop on Mathematical Natural Language Processing (MathNLP 2025)
CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
CoT-RAG: Integrating Chain of Thought and Retrieval-Augmented Generation to Enhance Reasoning in Large Language Models — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Counterfactual Debating with Preset Stances for Hallucination Elimination of LLMs — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
DAWN-ICL: Strategic Planning of Problem-solving Trajectories for Zero-Shot In-Context Learning — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
DiPT: Enhancing LLM Reasoning through Diversified Perspective-Taking — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
Do Large Language Model Benchmarks Test Reliability? — 2025 · arXiv:2502.03461
Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Error Classification of Large Language Models on Math Word Problems: A Dynamically Adaptive Framework — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Evaluating LLMs with Multiple Problems at once — 2025 · Proceedings of the Fourth Workshop on Generation, Evaluation and Metrics (GEM\texttwosuperior)
Evaluating Numeracy of Language Models as a Natural Language Inference Task — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
FLARE: Faithful Logic-Aided Reasoning and Exploration — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
First-Step Advantage: Importance of Starting Right in Multi-Step Math Reasoning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Generating Pedagogically Meaningful Visuals for Math Word Problems: A New Benchmark and Analysis of Text-to-Image Models — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Implicit Reasoning in Large Language Models: A Comprehensive Survey — 2025 · arXiv:2509.02350
Learning Text Styles: A Study on Transfer, Attribution, and Verification — 2025 · arXiv:2507.16530
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Make Every Penny Count: Difficulty-Adaptive Self-Consistency for Cost-Efficient Reasoning — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
Nudging: Inference-time Alignment of LLMs via Guided Decoding — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
On the Generalization vs Fidelity Paradox in Knowledge Distillation — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Persona is a Double-Edged Sword: Rethinking the Impact of Role-play Prompts in Zero-shot Reasoning Tasks — 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performance — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Propulsion: Steering LLM with Tiny Fine-Tuning — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
SIKeD: Self-guided Iterative Knowledge Distillation for Mathematical Reasoning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Self-Harmonized Chain of Thought — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Theorem Prover as a Judge for Synthetic Data Generation — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains — 2025 · arXiv:2505.16552
Tiny Budgets, Big Gains: Parameter Placement Strategy in Parameter Super-Efficient Fine-Tuning — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Towards Efficient CoT Distillation: Self-Guided Rationale Selector for Better Performance with Fewer Rationales — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models — 2025 · arXiv:2501.09686
UBench: Benchmarking Uncertainty in Large Language Models with Multiple Choice Questions — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter Efficient Fine-Tuning of Large Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Uncertainty-Aware Contrastive Decoding — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Understanding the Information Propagation Effects of Communication Topologies in LLM-based Multi-Agent Systems — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
When natural language is not enough: The limits of in-context learning demonstrations in multilingual reasoning — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
``Well, Keep Thinking'''': Enhancing LLM Reasoning with Adaptive Injection Decoding — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
A Tree-of-Thoughts to Broaden Multi-step Reasoning across Languages — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
Adaption-of-Thought: Learning Question Difficulty Improves Large Language Models for Reasoning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Adversarial Math Word Problem Generation — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Aligning Large and Small Language Models via Chain-of-Thought Reasoning — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Ask Again, Then Fail: Large Language Models'' Vacillations in Judgment — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Assessing Logical Puzzle Solving in Large Language Models: Insights from a Minesweeper Case Study — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Boosting Language Models Reasoning with Chain-of-Knowledge Prompting — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Chain-of-Thought Reasoning Without Prompting — 2024 · arXiv:2402.10200
ChatGPT Rates Natural Language Explanation Quality like Humans: But on Which Scales? — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Cutting Through the Noise: Boosting LLM Performance on Math Word Problems — our card · 2024 · arXiv:2406.15444
Don''t Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization — 2024 · arXiv:2403.18120
EXPLORA: Efficient Exemplar Subset Selection for Complex Reasoning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)
Empowering Multi-step Reasoning across Languages via Program-Aided Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning — 2024 · arXiv:2401.10480
Explicit Memory Learning with Expectation Maximization — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Exploring Reversal Mathematical Reasoning Ability for Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Fewer is More: Boosting Math Reasoning with Reinforced Context Pruning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
FinanceMATH: Knowledge-Intensive Math Reasoning in Finance Domains — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Forward-Backward Reasoning in Large Language Models for Mathematical Verification — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Improving Language Model Reasoning with Self-motivated Learning — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Instructing Large Language Models to Identify and Ignore Irrelevant Conditions — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Just Ask One More Time! Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Large Language Models for Mathematical Reasoning: Progresses and Challenges — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
Learning to Compress Prompt in Natural Language Formats — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
LoNAS: Elastic Low-Rank Adapters for Efficient Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Making Language Models Better Tool Learners with Execution Feedback — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems? — 2024 · arXiv:2403.14624
Meta-Cognitive Analysis: Evaluating Declarative and Procedural Knowledge in Datasets and Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving — 2024 · arXiv:2405.12205
MinT: Boosting Generalization in Mathematical Reasoning via Multi-view Fine-tuning — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Multi-Step Reasoning with Large Language Models, a Survey — 2024 · arXiv:2407.11511
Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers — 2024 · arXiv:2408.06195
NUMCoT: Numerals and Units of Measurement in Chain-of-Thought Reasoning using Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Orca-Math: Unlocking the potential of SLMs in Grade School Math — 2024 · arXiv:2402.14830
PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Heuristic-based Sampling — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuning — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Personality Alignment of Large Language Models — 2024 · arXiv:2408.11779
Prompt Engineering a Prompt Engineer — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
QDMR-based Planning-and-Solving Prompting for Complex Reasoning Tasks — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

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