Imagen de Portada

Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Lee, Sang-Woo, Yang, Sohee, Kwak, Donghyun, Siegel, Noah Y.
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence Computation and Language
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models
por: Siegel, Noah Y., et al.
Publicado: (2024)

LVLM-Compress-Bench: Benchmarking the Broader Impact of Large Vision-Language Model Compression
por: Kundu, Souvik, et al.
Publicado: (2025)

Unlocking the Potential of Diffusion Language Models through Template Infilling
por: Lee, Junhoo, et al.
Publicado: (2025)

Finding Answers in Thought Matters: Revisiting Evaluation on Large Language Models with Reasoning
por: Jo, Hwiyeol, et al.
Publicado: (2025)

Advancing Beyond Identification: Multi-bit Watermark for Large Language Models
por: Yoo, KiYoon, et al.
Publicado: (2023)

Language-Agnostic Suicidal Risk Detection Using Large Language Models
por: Kim, June-Woo, et al.
Publicado: (2025)

WoLF: Wide-scope Large Language Model Framework for CXR Understanding
por: Kang, Seil, et al.
Publicado: (2024)

Training Large Language Models to Predict Clinical Events
por: Turtel, Benjamin, et al.
Publicado: (2026)

Advancing Large Language Model Attribution through Self-Improving
por: Huang, Lei, et al.
Publicado: (2024)

Verbosity Tradeoffs and the Impact of Scale on the Faithfulness of LLM Self-Explanations
por: Siegel, Noah Y., et al.
Publicado: (2025)

Tokenization Matters! Degrading Large Language Models through Challenging Their Tokenization
por: Wang, Dixuan, et al.
Publicado: (2024)

Advancing the Robustness of Large Language Models through Self-Denoised Smoothing
por: Ji, Jiabao, et al.
Publicado: (2024)

Supernova Event Dataset: Interpreting Large Language Models' Personality through Critical Event Analysis
por: Agarwal, Pranav, et al.
Publicado: (2025)

Is Child-Directed Speech Effective Training Data for Language Models?
por: Feng, Steven Y., et al.
Publicado: (2024)

Understanding Moral Reasoning Trajectories in Large Language Models: Toward Probing-Based Explainability
por: Huang, Fan, et al.
Publicado: (2026)

Right to be Forgotten in the Era of Large Language Models: Implications, Challenges, and Solutions
por: Zhang, Dawen, et al.
Publicado: (2023)

Enhancing Building Semantics Preservation in AI Model Training with Large Language Model Encodings
por: Jang, Suhyung, et al.
Publicado: (2026)

Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning
por: Zhao, Yang, et al.
Publicado: (2024)

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning
por: Zhao, Hang, et al.
Publicado: (2024)

Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling
por: Gwak, Daehoon, et al.
Publicado: (2024)

Multimodal Forecasting of Sparse Intraoperative Hypotension Events Powered by Language Model
por: Zhang, Jintao, et al.
Publicado: (2025)

Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning
por: Bae, Sanghwan, et al.
Publicado: (2025)

SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language Models
por: Kim, SungHo, et al.
Publicado: (2026)

Large Language Model Reasoning Failures
por: Song, Peiyang, et al.
Publicado: (2026)

The Effect of Model Size on LLM Post-hoc Explainability via LIME
por: Heyen, Henning, et al.
Publicado: (2024)

Modeling Layered Consciousness with Multi-Agent Large Language Models
por: Kim, Sang Hun, et al.
Publicado: (2025)

We Need to Measure Data Diversity in NLP -- Better and Broader
por: Nguyen, Dong, et al.
Publicado: (2025)

How Well Can Reasoning Models Identify and Recover from Unhelpful Thoughts?
por: Yang, Sohee, et al.
Publicado: (2025)

Crowdsourcing with Enhanced Data Quality Assurance: An Efficient Approach to Mitigate Resource Scarcity Challenges in Training Large Language Models for Healthcare
por: Barai, P., et al.
Publicado: (2024)

Measuring the Impact of Lexical Training Data Coverage on Hallucination Detection in Large Language Models
por: Zhang, Shuo, et al.
Publicado: (2025)

Text2TimeSeries: Enhancing Financial Forecasting through Time Series Prediction Updates with Event-Driven Insights from Large Language Models
por: Kurisinkel, Litton Jose, et al.
Publicado: (2024)

Grading Massive Open Online Courses Using Large Language Models
por: Golchin, Shahriar, et al.
Publicado: (2024)

Legal Evalutions and Challenges of Large Language Models
por: Wang, Jiaqi, et al.
Publicado: (2024)

Improving Automatic Summarization of Radiology Reports through Mid-Training of Large Language Models
por: Lyu, Mengxian, et al.
Publicado: (2026)

Evaluating and Optimizing Educational Content with Large Language Model Judgments
por: He-Yueya, Joy, et al.
Publicado: (2024)

Advancing Mathematical Reasoning in Language Models: The Impact of Problem-Solving Data, Data Synthesis Methods, and Training Stages
por: Chen, Zui, et al.
Publicado: (2025)

Hierarchical Orthogonal Residual Spread for Precise Massive Editing in Large Language Models
por: Gu, Xiaojie, et al.
Publicado: (2026)

Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives
por: Hagos, Desta Haileselassie, et al.
Publicado: (2024)

Comparisons between a Large Language Model-based Real-Time Compound Diagnostic Medical AI Interface and Physicians for Common Internal Medicine Cases using Simulated Patients
por: Park, Hyungjun, et al.
Publicado: (2025)

Advancing AI with Integrity: Ethical Challenges and Solutions in Neural Machine Translation
por: Kimera, Richard, et al.
Publicado: (2024)