Cover Image

HYBRIDMIND: Meta Selection of Natural Language and Symbolic Language for Enhanced LLM Reasoning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Han, Simeng, Liu, Tianyu, Li, Chuhan, Xiong, Xuyuan, Cohan, Arman
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Evaluating Legal Reasoning Traces with Legal Issue Tree Rubrics
by: Lee, Jinu, et al.
Published: (2025)

Can Multimodal Foundation Models Understand Schematic Diagrams? An Empirical Study on Information-Seeking QA over Scientific Papers
by: Zhao, Yilun, et al.
Published: (2025)

MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs
by: Liu, Gabrielle Kaili-May, et al.
Published: (2025)

M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models
by: Li, Chuhan, et al.
Published: (2024)

TOMATO: Assessing Visual Temporal Reasoning Capabilities in Multimodal Foundation Models
by: Shangguan, Ziyao, et al.
Published: (2024)

On Evaluating LLM Alignment by Evaluating LLMs as Judges
by: Liu, Yixin, et al.
Published: (2025)

YaleNLP @ PerAnsSumm 2025: Multi-Perspective Integration via Mixture-of-Agents for Enhanced Healthcare QA Summarization
by: Jang, Dongsuk, et al.
Published: (2025)

FOLIO: Natural Language Reasoning with First-Order Logic
by: Han, Simeng, et al.
Published: (2022)

Natural Language Embedded Programs for Hybrid Language Symbolic Reasoning
by: Zhang, Tianhua, et al.
Published: (2023)

TESS 2: A Large-Scale Generalist Diffusion Language Model
by: Tae, Jaesung, et al.
Published: (2025)

Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models
by: Riddell, Martin, et al.
Published: (2024)

Benchmarking Generation and Evaluation Capabilities of Large Language Models for Instruction Controllable Summarization
by: Liu, Yixin, et al.
Published: (2023)

Demystifying Scientific Problem-Solving in LLMs by Probing Knowledge and Reasoning
by: Li, Alan, et al.
Published: (2025)

NExT: Teaching Large Language Models to Reason about Code Execution
by: Ni, Ansong, et al.
Published: (2024)

Table-R1: Inference-Time Scaling for Table Reasoning
by: Yang, Zheyuan, et al.
Published: (2025)

Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language Models
by: Wang, Yiming, et al.
Published: (2023)

SUCEA: Reasoning-Intensive Retrieval for Adversarial Fact-checking through Claim Decomposition and Editing
by: Liu, Hongjun, et al.
Published: (2025)

Dancing with Critiques: Enhancing LLM Reasoning with Stepwise Natural Language Self-Critique
by: Li, Yansi, et al.
Published: (2025)

Observable Propagation: Uncovering Feature Vectors in Transformers
by: Dunefsky, Jacob, et al.
Published: (2023)

MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning
by: Tang, Xiangru, et al.
Published: (2023)

Understanding Reference Policies in Direct Preference Optimization
by: Liu, Yixin, et al.
Published: (2024)

MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree Search
by: Hu, Yunhai, et al.
Published: (2025)

Bayesian Calibration of Win Rate Estimation with LLM Evaluators
by: Gao, Yicheng, et al.
Published: (2024)

SymBa: Symbolic Backward Chaining for Structured Natural Language Reasoning
by: Lee, Jinu, et al.
Published: (2024)

Calibrating Long-form Generations from Large Language Models
by: Huang, Yukun, et al.
Published: (2024)

Patient-Similarity Cohort Reasoning in Clinical Text-to-SQL
by: Shen, Yifei, et al.
Published: (2026)

Investigating Data Contamination in Modern Benchmarks for Large Language Models
by: Deng, Chunyuan, et al.
Published: (2023)

Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models
by: Wu, Junjie, et al.
Published: (2025)

HumanEval Pro and MBPP Pro: Evaluating Large Language Models on Self-invoking Code Generation
by: Yu, Zhaojian, et al.
Published: (2024)

ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning
by: Tang, Xiangru, et al.
Published: (2025)

FinanceMath: Knowledge-Intensive Math Reasoning in Finance Domains
by: Zhao, Yilun, et al.
Published: (2023)

From Hypothesis to Premises: LLM-based Backward Logical Reasoning with Selective Symbolic Translation
by: Li, Qingchuan, et al.
Published: (2025)

SciDQA: A Deep Reading Comprehension Dataset over Scientific Papers
by: Singh, Shruti, et al.
Published: (2024)

P-FOLIO: Evaluating and Improving Logical Reasoning with Abundant Human-Written Reasoning Chains
by: Han, Simeng, et al.
Published: (2024)

Discovering a Shared Logical Subspace: Steering LLM Logical Reasoning via Alignment of Natural-Language and Symbolic Views
by: Fang, Feihao, et al.
Published: (2026)

Optimizing Language Model's Reasoning Abilities with Weak Supervision
by: Tong, Yongqi, et al.
Published: (2024)

ATEB: Evaluating and Improving Advanced NLP Tasks for Text Embedding Models
by: Han, Simeng, et al.
Published: (2025)

AlphaResearch: Accelerating New Algorithm Discovery with Language Models
by: Yu, Zhaojian, et al.
Published: (2025)

On Learning to Summarize with Large Language Models as References
by: Liu, Yixin, et al.
Published: (2023)

COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences
by: Liu, Yixin, et al.
Published: (2024)