Cover Image

Literature Meets Data: A Synergistic Approach to Hypothesis Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Haokun, Zhou, Yangqiaoyu, Li, Mingxuan, Yuan, Chenfei, Tan, Chenhao
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Computation and Language Computers and Society Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hypothesis Generation with Large Language Models
by: Zhou, Yangqiaoyu, et al.
Published: (2024)

HypoBench: Towards Systematic and Principled Benchmarking for Hypothesis Generation
by: Liu, Haokun, et al.
Published: (2025)

HypoEval: Hypothesis-Guided Evaluation for Natural Language Generation
by: Li, Mingxuan, et al.
Published: (2025)

On the Effectiveness and Generalization of Race Representations for Debiasing High-Stakes Decisions
by: Nguyen, Dang, et al.
Published: (2025)

Know Thyself? On the Incapability and Implications of AI Self-Recognition
by: Bai, Xiaoyan, et al.
Published: (2025)

CaseSumm: A Large-Scale Dataset for Long-Context Summarization from U.S. Supreme Court Opinions
by: Heddaya, Mourad, et al.
Published: (2024)

The Story is Not the Science: Execution-Grounded Evaluation of Mechanistic Interpretability Research
by: Bai, Xiaoyan, et al.
Published: (2026)

Superficial Safety Alignment Hypothesis
by: Li, Jianwei, et al.
Published: (2024)

DualAlign: Generating Clinically Grounded Synthetic Data
by: Li, Rumeng, et al.
Published: (2025)

Causal Reasoning and Large Language Models: Opening a New Frontier for Causality
by: Kıcıman, Emre, et al.
Published: (2023)

The Lock-in Hypothesis: Stagnation by Algorithm
by: Qiu, Tianyi Alex, et al.
Published: (2025)

Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge Graphs
by: Shang, Tianqi, et al.
Published: (2024)

Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
by: Zhu, Zhaowei, et al.
Published: (2023)

Embedding Enhancement via Fine-Tuned Language Models for Learner-Item Cognitive Modeling
by: Liu, Yuanhao, et al.
Published: (2026)

Integrating LSTM and BERT for Long-Sequence Data Analysis in Intelligent Tutoring Systems
by: Li, Zhaoxing, et al.
Published: (2024)

Language Representation Favored Zero-Shot Cross-Domain Cognitive Diagnosis
by: Liu, Shuo, et al.
Published: (2025)

Exploring Accuracy-Fairness Trade-off in Large Language Models
by: Zhang, Qingquan, et al.
Published: (2024)

Multimodal Assessment of Classroom Discourse Quality: A Text-Centered Attention-Based Multi-Task Learning Approach
by: Hou, Ruikun, et al.
Published: (2025)

On the Detectability of LLM-Generated Text: What Exactly Is LLM-Generated Text?
by: Geng, Mingmeng, et al.
Published: (2025)

Sentiment Analysis of Cyberbullying Data in Social Media
by: Susmitha, Arvapalli Sai, et al.
Published: (2024)

LLMCO2: Advancing Accurate Carbon Footprint Prediction for LLM Inferences
by: Fu, Zhenxiao, et al.
Published: (2024)

Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments
by: Zhou, Han, et al.
Published: (2024)

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI
by: Yang, Chao, et al.
Published: (2024)

Impacts of Racial Bias in Historical Training Data for News AI
by: Bhargava, Rahul, et al.
Published: (2025)

Towards Robust Evaluation of Unlearning in LLMs via Data Transformations
by: Joshi, Abhinav, et al.
Published: (2024)

Position: The Most Expensive Part of an LLM should be its Training Data
by: Kandpal, Nikhil, et al.
Published: (2025)

Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey
by: Dong, Zhichen, et al.
Published: (2024)

Generative AI Meets Future Cities: Towards an Era of Autonomous Urban Intelligence
by: Wang, Dongjie, et al.
Published: (2023)

Towards Enriched Controllability for Educational Question Generation
by: Leite, Bernardo, et al.
Published: (2023)

Thinking Outside the (Gray) Box: A Context-Based Score for Assessing Value and Originality in Neural Text Generation
by: Franceschelli, Giorgio, et al.
Published: (2025)

Peeking Behind Closed Doors: Risks of LLM Evaluation by Private Data Curators
by: Bansal, Hritik, et al.
Published: (2025)

Understanding and Mitigating Risks of Generative AI in Financial Services
by: Gehrmann, Sebastian, et al.
Published: (2025)

Prompt-Counterfactual Explanations for Generative AI System Behavior
by: Goethals, Sofie, et al.
Published: (2026)

Implementing a Nordic-Baltic Federated Health Data Network: a case report
by: Chomutare, Taridzo, et al.
Published: (2024)

Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
by: Shieh, Evan, et al.
Published: (2024)

Standardizing Intelligence: Aligning Generative AI for Regulatory and Operational Compliance
by: Imperial, Joseph Marvin, et al.
Published: (2025)

Assessing Generalization for Subpopulation Representative Modeling via In-Context Learning
by: Simmons, Gabriel, et al.
Published: (2024)

Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy
by: Tang, Xiangru, et al.
Published: (2024)

Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation
by: Wang, Jiawei, et al.
Published: (2024)

Richer Output for Richer Countries: Uncovering Geographical Disparities in Generated Stories and Travel Recommendations
by: Bhagat, Kirti, et al.
Published: (2024)