Cover Image

CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhen, Hao, Yang, Jidong J.
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Leveraging Large Language Models with Chain-of-Thought and Prompt Engineering for Traffic Crash Severity Analysis and Inference
by: Zhen, Hao, et al.
Published: (2024)

Feature Group Tabular Transformer: A Novel Approach to Traffic Crash Modeling and Causality Analysis
by: Lares, Oscar, et al.
Published: (2024)

CrashChat: A Multimodal Large Language Model for Multitask Traffic Crash Video Analysis
by: Liang, Kaidi, et al.
Published: (2025)

Automating Crash Diagram Generation Using Vision-Language Models: A Case Study on Multi-Lane Roundabouts
by: Lu, Xiao, et al.
Published: (2026)

Improving Crash Data Quality with Large Language Models: Evidence from Secondary Crash Narratives in Kentucky
by: Zhang, Xu, et al.
Published: (2025)

Exploring Large Language Models in Resolving Environment-Related Crash Bugs: Localizing and Repairing
by: Du, Xueying, et al.
Published: (2023)

Temporal Relational Reasoning of Large Language Models for Detecting Stock Portfolio Crashes
by: Koa, Kelvin J. L., et al.
Published: (2024)

Accuracy is Not Agreement: Expert-Aligned Evaluation of Crash Narrative Classification Models
by: Bhagat, Sudesh Ramesh, et al.
Published: (2025)

Towards Reliable and Interpretable Traffic Crash Pattern Prediction and Safety Interventions Using Customized Large Language Models
by: Zhao, Yang, et al.
Published: (2025)

Advanced Assistance for Traffic Crash Analysis: An AI-Driven Multi-Agent Approach to Pre-Crash Reconstruction
by: Xu, Gerui, et al.
Published: (2025)

Hypothesis Testing Prompting Improves Deductive Reasoning in Large Language Models
by: Li, Yitian, et al.
Published: (2024)

CrashSight: A Phase-Aware, Infrastructure-Centric Video Benchmark for Traffic Crash Scene Understanding and Reasoning
by: Gan, Rui, et al.
Published: (2026)

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference
by: Yang, Yunxiang, et al.
Published: (2025)

Identification of Potentially Misclassified Crash Narratives using Machine Learning (ML) and Deep Learning (DL)
by: Bhagat, Sudesh, et al.
Published: (2025)

Contextualization Distillation from Large Language Model for Knowledge Graph Completion
by: Li, Dawei, et al.
Published: (2024)

Look Before You Leap: Problem Elaboration Prompting Improves Mathematical Reasoning in Large Language Models
by: Liao, Haoran, et al.
Published: (2024)

Ctrl-Crash: Controllable Diffusion for Realistic Car Crashes
by: Gosselin, Anthony, et al.
Published: (2025)

"Lost-in-the-Later": Framework for Quantifying Contextual Grounding in Large Language Models
by: Tao, Yufei, et al.
Published: (2025)

Multi-view Phase-aware Pedestrian-Vehicle Incident Reasoning Framework with Vision-Language Models
by: Zhen, Hao, et al.
Published: (2025)

Systematic Comparative Analysis of Large Pretrained Language Models on Contextualized Medication Event Extraction
by: Abdul-Quddoos, Tariq, et al.
Published: (2025)

METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models
by: Li, Pengfeng, et al.
Published: (2026)

Interpreting Public Sentiment in Diplomacy Events: A Counterfactual Analysis Framework Using Large Language Models
by: Ouyang, Leyi
Published: (2025)

Large Language Models for Crash Detection in Video: A Survey of Methods, Datasets, and Challenges
by: Akter, Sanjeda, et al.
Published: (2025)

Large Language Models for Mathematical Analysis
by: Chen, Ziye, et al.
Published: (2024)

A Human-Centered Workflow for Using Large Language Models in Content Analysis
by: Zupic, Ivan
Published: (2026)

What Is Missing: Interpretable Ratings for Large Language Model Outputs
by: Stranges, Nicholas, et al.
Published: (2026)

Contextual Augmentation for Entity Linking using Large Language Models
by: Vollmers, Daniel, et al.
Published: (2025)

Contextual Reinforcement in Multimodal Token Compression for Large Language Models
by: Piero, Naderdel, et al.
Published: (2025)

From Narratives to Probabilistic Reasoning: Predicting and Interpreting Drivers' Hazardous Actions in Crashes Using Large Language Model
by: Chen, Boyou, et al.
Published: (2025)

CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor
by: Xu, Zhenhua, et al.
Published: (2025)

Mechanistic Interpretability of GPT-2: Lexical and Contextual Layers in Sentiment Analysis
by: Hatua, Amartya
Published: (2025)

LLMD: A Large Language Model for Interpreting Longitudinal Medical Records
by: Porter, Robert, et al.
Published: (2024)

Multi-Scale Manifold Alignment for Interpreting Large Language Models: A Unified Information-Geometric Framework
by: Zhang, Yukun, et al.
Published: (2025)

Attention Basin: Why Contextual Position Matters in Large Language Models
by: Yi, Zihao, et al.
Published: (2025)

Enhancing Contextual Understanding in Large Language Models through Contrastive Decoding
by: Zhao, Zheng, et al.
Published: (2024)

Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases
by: Asiedu, Mercy, et al.
Published: (2024)

Integration of Explainable AI Techniques with Large Language Models for Enhanced Interpretability for Sentiment Analysis
by: Thogesan, Thivya, et al.
Published: (2025)

CrashFormer: A Multimodal Architecture to Predict the Risk of Crash
by: Monsefi, Amin Karimi, et al.
Published: (2024)

A Comprehensive Evaluation of Large Language Models on Aspect-Based Sentiment Analysis
by: Zhou, Changzhi, et al.
Published: (2024)

Morality is Contextual: Learning Interpretable Moral Contexts from Human Data with Probabilistic Clustering and Large Language Models
by: Morlat, Geoffroy, et al.
Published: (2025)