QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation
Fuente:
arXiv
Guardado en:
| Autores principales: | Li, Jiazheng, Lin, Hongzhou, Lu, Hong, Wen, Kaiyue, Yang, Zaiwen, Gao, Jiaxuan, Wu, Yi, Zhang, Jingzhao |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency
por: Wen, Kaiyue, et al.
Publicado: (2024)
por: Wen, Kaiyue, et al.
Publicado: (2024)
Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
por: Gu, Xinran, et al.
Publicado: (2025)
por: Gu, Xinran, et al.
Publicado: (2025)
Benchmarking LLMs' Mathematical Reasoning with Unseen Random Variables Questions
por: Hong, Zijin, et al.
Publicado: (2025)
por: Hong, Zijin, et al.
Publicado: (2025)
KAG-Thinker: Interactive Thinking and Deep Reasoning in LLMs via Knowledge-Augmented Generation
por: Zhang, Dalong, et al.
Publicado: (2025)
por: Zhang, Dalong, et al.
Publicado: (2025)
NeuralDB: Scaling Knowledge Editing in LLMs to 100,000 Facts with Neural KV Database
por: Fei, Weizhi, et al.
Publicado: (2025)
por: Fei, Weizhi, et al.
Publicado: (2025)
How Far Are We from Optimal Reasoning Efficiency?
por: Gao, Jiaxuan, et al.
Publicado: (2025)
por: Gao, Jiaxuan, et al.
Publicado: (2025)
CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering
por: Wiratunga, Nirmalie, et al.
Publicado: (2024)
por: Wiratunga, Nirmalie, et al.
Publicado: (2024)
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
por: Yue, Yang, et al.
Publicado: (2025)
por: Yue, Yang, et al.
Publicado: (2025)
QPaug: Question and Passage Augmentation for Open-Domain Question Answering of LLMs
por: Kim, Minsang, et al.
Publicado: (2024)
por: Kim, Minsang, et al.
Publicado: (2024)
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
por: Wang, Suyuchen, et al.
Publicado: (2025)
por: Wang, Suyuchen, et al.
Publicado: (2025)
CHOPS: CHat with custOmer Profile Systems for Customer Service with LLMs
por: Shi, Jingzhe, et al.
Publicado: (2024)
por: Shi, Jingzhe, et al.
Publicado: (2024)
Zero-shot Graph Reasoning via Retrieval Augmented Framework with LLMs
por: Li, Hanqing, et al.
Publicado: (2025)
por: Li, Hanqing, et al.
Publicado: (2025)
Know Your Needs Better: Towards Structured Understanding of Marketer Demands with Analogical Reasoning Augmented LLMs
por: Wang, Junjie, et al.
Publicado: (2024)
por: Wang, Junjie, et al.
Publicado: (2024)
Knowledge Tagging System on Math Questions via LLMs with Flexible Demonstration Retriever
por: Li, Hang, et al.
Publicado: (2024)
por: Li, Hang, et al.
Publicado: (2024)
Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering
por: Wang, Yubo, et al.
Publicado: (2023)
por: Wang, Yubo, et al.
Publicado: (2023)
The Potential of LLMs in Medical Education: Generating Questions and Answers for Qualification Exams
por: Zhu, Yunqi, et al.
Publicado: (2024)
por: Zhu, Yunqi, et al.
Publicado: (2024)
Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering
por: Zhang, Yichi, et al.
Publicado: (2023)
por: Zhang, Yichi, et al.
Publicado: (2023)
Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
por: Xu, Jing, et al.
Publicado: (2024)
por: Xu, Jing, et al.
Publicado: (2024)
SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
por: Xu, Bin, et al.
Publicado: (2024)
por: Xu, Bin, et al.
Publicado: (2024)
AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
por: Gao, Silin, et al.
Publicado: (2025)
por: Gao, Silin, et al.
Publicado: (2025)
MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs
por: Lu, Zimu, et al.
Publicado: (2024)
por: Lu, Zimu, et al.
Publicado: (2024)
Time-R1: Towards Comprehensive Temporal Reasoning in LLMs
por: Liu, Zijia, et al.
Publicado: (2025)
por: Liu, Zijia, et al.
Publicado: (2025)
From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning
por: Yang, Cheng, et al.
Publicado: (2025)
por: Yang, Cheng, et al.
Publicado: (2025)
ARise: Towards Knowledge-Augmented Reasoning via Risk-Adaptive Search
por: Zhang, Yize, et al.
Publicado: (2025)
por: Zhang, Yize, et al.
Publicado: (2025)
MolQuest: A Benchmark for Agentic Evaluation of Abductive Reasoning in Chemical Structure Elucidation
por: Han, Taolin, et al.
Publicado: (2026)
por: Han, Taolin, et al.
Publicado: (2026)
Generative Data Augmentation using LLMs improves Distributional Robustness in Question Answering
por: Chowdhury, Arijit Ghosh, et al.
Publicado: (2023)
por: Chowdhury, Arijit Ghosh, et al.
Publicado: (2023)
Large-Scale Constraint Generation -- Can LLMs Parse Hundreds of Constraints?
por: Boffa, Matteo, et al.
Publicado: (2025)
por: Boffa, Matteo, et al.
Publicado: (2025)
KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation
por: Liang, Lei, et al.
Publicado: (2024)
por: Liang, Lei, et al.
Publicado: (2024)
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature
por: Li, Dawei, et al.
Publicado: (2024)
por: Li, Dawei, et al.
Publicado: (2024)
TextQuests: How Good are LLMs at Text-Based Video Games?
por: Phan, Long, et al.
Publicado: (2025)
por: Phan, Long, et al.
Publicado: (2025)
Qworld: Question-Specific Evaluation Criteria for LLMs
por: Gao, Shanghua, et al.
Publicado: (2026)
por: Gao, Shanghua, et al.
Publicado: (2026)
Kwai-STaR: Transform LLMs into State-Transition Reasoners
por: Lu, Xingyu, et al.
Publicado: (2024)
por: Lu, Xingyu, et al.
Publicado: (2024)
Augmenting Question Answering with A Hybrid RAG Approach
por: Yang, Tianyi, et al.
Publicado: (2026)
por: Yang, Tianyi, et al.
Publicado: (2026)
From Reasoning to Generalization: Knowledge-Augmented LLMs for ARC Benchmark
por: Lei, Chao, et al.
Publicado: (2025)
por: Lei, Chao, et al.
Publicado: (2025)
Towards Human-Like Grading: A Unified LLM-Enhanced Framework for Subjective Question Evaluation
por: Zhua, Fanwei, et al.
Publicado: (2025)
por: Zhua, Fanwei, et al.
Publicado: (2025)
Acting Flatterers via LLMs Sycophancy: Combating Clickbait with LLMs Opposing-Stance Reasoning
por: Zhang, Chaowei, et al.
Publicado: (2026)
por: Zhang, Chaowei, et al.
Publicado: (2026)
Retrieval Augmented Question Answering: When Should LLMs Admit Ignorance?
por: Wang, Dingmin, et al.
Publicado: (2025)
por: Wang, Dingmin, et al.
Publicado: (2025)
MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
por: Wu, Juncheng, et al.
Publicado: (2025)
por: Wu, Juncheng, et al.
Publicado: (2025)
Quest: Query-centric Data Synthesis Approach for Long-context Scaling of Large Language Model
por: Gao, Chaochen, et al.
Publicado: (2024)
por: Gao, Chaochen, et al.
Publicado: (2024)
Router-R1: Teaching LLMs Multi-Round Routing and Aggregation via Reinforcement Learning
por: Zhang, Haozhen, et al.
Publicado: (2025)
por: Zhang, Haozhen, et al.
Publicado: (2025)
Ejemplares similares
-
From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency
por: Wen, Kaiyue, et al.
Publicado: (2024) -
Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
por: Gu, Xinran, et al.
Publicado: (2025) -
Benchmarking LLMs' Mathematical Reasoning with Unseen Random Variables Questions
por: Hong, Zijin, et al.
Publicado: (2025) -
KAG-Thinker: Interactive Thinking and Deep Reasoning in LLMs via Knowledge-Augmented Generation
por: Zhang, Dalong, et al.
Publicado: (2025) -
NeuralDB: Scaling Knowledge Editing in LLMs to 100,000 Facts with Neural KV Database
por: Fei, Weizhi, et al.
Publicado: (2025)