Cover Image

Relevant or Random: Can LLMs Truly Perform Analogical Reasoning?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Qin, Chengwei, Xia, Wenhan, Wang, Tan, Jiao, Fangkai, Hu, Yuchen, Ding, Bosheng, Chen, Ruirui, Joty, Shafiq
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

Beyond Output Matching: Bidirectional Alignment for Enhanced In-Context Learning
by: Qin, Chengwei, et al.
Published: (2023)

Lifelong Event Detection with Embedding Space Separation and Compaction
by: Qin, Chengwei, et al.
Published: (2024)

Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing
by: Jiao, Fangkai, et al.
Published: (2024)

StructTest: Benchmarking LLMs' Reasoning through Compositional Structured Outputs
by: Chen, Hailin, et al.
Published: (2024)

A Comprehensive Survey of Contamination Detection Methods in Large Language Models
by: Ravaut, Mathieu, et al.
Published: (2024)

Exploring Self-supervised Logic-enhanced Training for Large Language Models
by: Jiao, Fangkai, et al.
Published: (2023)

Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks
by: Li, Xingxuan, et al.
Published: (2024)

CoMMET: To What Extent Can LLMs Perform Theory of Mind Tasks?
by: Chen, Ruirui, et al.
Published: (2026)

Data Augmentation using Large Language Models: Data Perspectives, Learning Paradigms and Challenges
by: Ding, Bosheng, et al.
Published: (2024)

ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?
by: Chen, Hailin, et al.
Published: (2023)

Preference Optimization for Reasoning with Pseudo Feedback
by: Jiao, Fangkai, et al.
Published: (2024)

A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems
by: Ke, Zixuan, et al.
Published: (2025)

Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources
by: Li, Xingxuan, et al.
Published: (2023)

Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning
by: Xia, Wenhan, et al.
Published: (2024)

Theory of Mind in Large Language Models: Assessment and Enhancement
by: Chen, Ruirui, et al.
Published: (2025)

Personalised Distillation: Empowering Open-Sourced LLMs with Adaptive Learning for Code Generation
by: Chen, Hailin, et al.
Published: (2023)

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization
by: Li, Chuyuan, et al.
Published: (2025)

VIBEPASS: Can Vibe Coders Really Pass the Vibe Check?
by: Bansal, Srijan, et al.
Published: (2026)

Unsupervised Summarization Re-ranking
by: Ravaut, Mathieu, et al.
Published: (2022)

Unlocking Temporal Question Answering for Large Language Models with Tailor-Made Reasoning Logic
by: Li, Xingxuan, et al.
Published: (2023)

ChartInstruct: Instruction Tuning for Chart Comprehension and Reasoning
by: Masry, Ahmed, et al.
Published: (2024)

NAACL2025 Tutorial: Adaptation of Large Language Models
by: Ke, Zixuan, et al.
Published: (2025)

Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts
by: Nguyen, Xuan-Phi, et al.
Published: (2023)

Describe-then-Reason: Improving Multimodal Mathematical Reasoning through Visual Comprehension Training
by: Jia, Mengzhao, et al.
Published: (2024)

On Context Utilization in Summarization with Large Language Models
by: Ravaut, Mathieu, et al.
Published: (2023)

On Positional Bias of Faithfulness for Long-form Summarization
by: Wan, David, et al.
Published: (2024)

JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking
by: Niu, Tong, et al.
Published: (2024)

Demystifying Hybrid Thinking: Can LLMs Truly Switch Between Think and No-Think?
by: Wang, Shouren, et al.
Published: (2025)

LLMs as Models for Analogical Reasoning
by: Musker, Sam, et al.
Published: (2024)

Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction
by: Shi, Zhenmei, et al.
Published: (2024)

Demystifying Domain-adaptive Post-training for Financial LLMs
by: Ke, Zixuan, et al.
Published: (2025)

Direct Judgement Preference Optimization
by: Wang, Peifeng, et al.
Published: (2024)

ParaICL: Towards Parallel In-Context Learning
by: Li, Xingxuan, et al.
Published: (2024)

SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning
by: Wang, Bin, et al.
Published: (2023)

Can LLMs Improve Multimodal Fact-Checking by Asking Relevant Questions?
by: Beigi, Alimohammad, et al.
Published: (2024)

ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild
by: Masry, Ahmed, et al.
Published: (2024)

CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules
by: Le, Hung, et al.
Published: (2023)

LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs
by: Long, Do Xuan, et al.
Published: (2024)

Evaluating Judges as Evaluators: The JETTS Benchmark of LLM-as-Judges as Test-Time Scaling Evaluators
by: Zhou, Yilun, et al.
Published: (2025)

Investigating Factuality in Long-Form Text Generation: The Roles of Self-Known and Self-Unknown
by: Tu, Lifu, et al.
Published: (2024)