Cover Image

Evidence Is All You Need: Ordering Imaging Studies via Language Model Alignment with the ACR Appropriateness Criteria

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yao, Michael S., Chae, Allison, Kahn Jr., Charles E., Witschey, Walter R., Gee, James C., Sagreiya, Hersh, Bastani, Osbert
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computation and Language Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Human Sequential Decision-Making with Reinforcement Learning
by: Bastani, Hamsa, et al.
Published: (2021)

Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings
by: Xu, Kan, et al.
Published: (2021)

Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
by: Yao, Michael S., et al.
Published: (2025)

Prior-Agnostic Incentive-Compatible Exploration
by: Ramalingam, Ramya, et al.
Published: (2026)

CopilotCAD: Empowering Radiologists with Report Completion Models and Quantitative Evidence from Medical Image Foundation Models
by: Wang, Sheng, et al.
Published: (2024)

Improving Structural Diversity of Blackbox LLMs via Chain-of-Specification Prompting
by: Young, Halley, et al.
Published: (2024)

TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction
by: Li, Shuo, et al.
Published: (2023)

Metaheuristics is All You Need
by: Cuicizion, Eliuvish, et al.
Published: (2024)

Asymptotic Normality of Generalized Low-Rank Matrix Sensing via Riemannian Geometry
by: Bastani, Osbert
Published: (2024)

One-Shot Safety Alignment for Large Language Models via Optimal Dualization
by: Huang, Xinmeng, et al.
Published: (2024)

Reinforcement Learning for Clinical Reasoning: Aligning LLMs with ACR Imaging Appropriateness Criteria
by: Tziakouri, Anni, et al.
Published: (2025)

Generative Adversarial Model-Based Optimization via Source Critic Regularization
by: Yao, Michael S., et al.
Published: (2024)

A Single Simple Patch is All You Need for AI-generated Image Detection
by: Chen, Jiaxuan, et al.
Published: (2024)

Intention Is All You Need
by: Sarkar, Advait
Published: (2024)

Contrast Is All You Need
by: Kilic, Burak, et al.
Published: (2023)

Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models
by: Tyukin, Georgy, et al.
Published: (2024)

Not Everything is All You Need: Toward Low-Redundant Optimization for Large Language Model Alignment
by: Chen, Zhipeng, et al.
Published: (2024)

Tensor Product Attention Is All You Need
by: Zhang, Yifan, et al.
Published: (2025)

"All You Need" is Not All You Need for a Paper Title: On the Origins of a Scientific Meme
by: Alyakin, Anton
Published: (2025)

[MASK] is All You Need
by: Hu, Vincent Tao, et al.
Published: (2024)

Not All Tokens Are What You Need In Thinking
by: Yuan, Hang, et al.
Published: (2025)

Increasing the Thinking Budget is Not All You Need
by: Iacobacci, Ignacio, et al.
Published: (2025)

Pairwise Comparisons Are All You Need
by: Chahine, Nicolas, et al.
Published: (2024)

Training on the Benchmark Is Not All You Need
by: Ni, Shiwen, et al.
Published: (2024)

Similarity Memory Prior is All You Need for Medical Image Segmentation
by: Tang, Hao, et al.
Published: (2025)

All You Need to Know About Training Image Retrieval Models
by: Berton, Gabriele, et al.
Published: (2025)

Cooperation Is All You Need
by: Adeel, Ahsan, et al.
Published: (2023)

PopPy: Opportunistically Exploiting Parallelism in Python Compound AI Applications
by: Mell, Stephen, et al.
Published: (2026)

Not All Preferences are What You Need for Post-Training: Selective Alignment Strategy for Preference Optimization
by: Dong, Zhijin
Published: (2025)

Rethinking Learned Image Compression: Context is All You Need
by: Luo, Jixiang
Published: (2024)

Text Embedding is Not All You Need: Attention Control for Text-to-Image Semantic Alignment with Text Self-Attention Maps
by: Kim, Jeeyung, et al.
Published: (2024)

Evaluating the Diversity and Quality of LLM Generated Content
by: Shypula, Alexander, et al.
Published: (2025)

HCC Is All You Need: Alignment-The Sensible Kind Anyway-Is Just Human-Centered Computing
by: Gilbert, Eric
Published: (2024)

Relevance Isn't All You Need: Scaling RAG Systems With Inference-Time Compute Via Multi-Criteria Reranking
by: LeVine, Will, et al.
Published: (2025)

Zoom and Shift are All You Need
by: Qin, Jiahao
Published: (2024)

More Agents Is All You Need
by: Li, Junyou, et al.
Published: (2024)

CORDIC Is All You Need
by: Kokane, Omkar, et al.
Published: (2025)

Markov Renewal Proportional Hazards is All You Need
by: Cui, Elvis Han
Published: (2025)

A Single Image and Multimodality Is All You Need for Novel View Synthesis
by: Javadi, Amirhosein, et al.
Published: (2026)

ParameterNet: Parameters Are All You Need
by: Han, Kai, et al.
Published: (2023)