Saved in:
| Main Authors: | Liang, Zhongyuan, Suresh, Arvind, Chen, Irene Y. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.19625 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Do Sparse Autoencoders Identify Reasoning Features in Language Models?
by: Ma, George, et al.
Published: (2026)
by: Ma, George, et al.
Published: (2026)
OC-Distill: Ontology-aware Contrastive Learning with Cross-Modal Distillation for ICU Risk Prediction
by: Liang, Zhongyuan, et al.
Published: (2026)
by: Liang, Zhongyuan, et al.
Published: (2026)
ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks
by: Zhu, Yinghao, et al.
Published: (2024)
by: Zhu, Yinghao, et al.
Published: (2024)
Hybrid Meta-learners for Estimating Heterogeneous Treatment Effects
by: Liang, Zhongyuan, et al.
Published: (2025)
by: Liang, Zhongyuan, et al.
Published: (2025)
Using Machine Bias To Measure Human Bias
by: Dong, Wanxue, et al.
Published: (2024)
by: Dong, Wanxue, et al.
Published: (2024)
Large Language Models Streamline Automated Machine Learning for Clinical Studies
by: Arasteh, Soroosh Tayebi, et al.
Published: (2023)
by: Arasteh, Soroosh Tayebi, et al.
Published: (2023)
Linear Dynamics in the RLVR Training of Large Language Models
by: Wang, Tianle, et al.
Published: (2026)
by: Wang, Tianle, et al.
Published: (2026)
Learning to Make Adherence-Aware Advice
by: Chen, Guanting, et al.
Published: (2023)
by: Chen, Guanting, et al.
Published: (2023)
Identifying Reasons for Contraceptive Switching from Real-World Data Using Large Language Models
by: Miao, Brenda Y., et al.
Published: (2024)
by: Miao, Brenda Y., et al.
Published: (2024)
Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models
by: Demircan, Can, et al.
Published: (2024)
by: Demircan, Can, et al.
Published: (2024)
Revealing Multimodal Causality with Large Language Models
by: Li, Jin, et al.
Published: (2025)
by: Li, Jin, et al.
Published: (2025)
How Can We Diagnose and Treat Bias in Large Language Models for Clinical Decision-Making?
by: Benkirane, Kenza, et al.
Published: (2024)
by: Benkirane, Kenza, et al.
Published: (2024)
Unrewarded Exploration in Large Language Models Reveals Latent Learning from Psychology
by: Xiong, Jian, et al.
Published: (2026)
by: Xiong, Jian, et al.
Published: (2026)
Utilizing Large Language Models for Machine Learning Explainability
by: Vassiliades, Alexandros, et al.
Published: (2025)
by: Vassiliades, Alexandros, et al.
Published: (2025)
ACE-RLHF: Automated Code Evaluation and Socratic Feedback Generation Tool using Large Language Models and Reinforcement Learning with Human Feedback
by: Rahman, Tasnia, et al.
Published: (2025)
by: Rahman, Tasnia, et al.
Published: (2025)
ICAD-LLM: One-for-All Anomaly Detection via In-Context Learning with Large Language Models
by: Wu, Zhongyuan, et al.
Published: (2025)
by: Wu, Zhongyuan, et al.
Published: (2025)
Multimodal Machine Learning in Image-Based and Clinical Biomedicine: Survey and Prospects
by: Warner, Elisa, et al.
Published: (2023)
by: Warner, Elisa, et al.
Published: (2023)
Attribution-Guided Masking for Robust Cross-Domain Sentiment Classification
by: Harkare, Shubham, et al.
Published: (2026)
by: Harkare, Shubham, et al.
Published: (2026)
Large Language Model Enhanced Machine Learning Estimators for Classification
by: Wu, Yuhang, et al.
Published: (2024)
by: Wu, Yuhang, et al.
Published: (2024)
CogGPT: Unleashing the Power of Cognitive Dynamics on Large Language Models
by: Lv, Yaojia, et al.
Published: (2024)
by: Lv, Yaojia, et al.
Published: (2024)
Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models
by: Antari, Ahmad, et al.
Published: (2025)
by: Antari, Ahmad, et al.
Published: (2025)
Using Large Language Models to Automate and Expedite Reinforcement Learning with Reward Machine
by: Alsadat, Shayan Meshkat, et al.
Published: (2024)
by: Alsadat, Shayan Meshkat, et al.
Published: (2024)
RFID based Health Adherence Medicine Case Using Fair Federated Learning
by: khodaei, Ali Kamrani, et al.
Published: (2024)
by: khodaei, Ali Kamrani, et al.
Published: (2024)
Physics Event Classification Using Large Language Models
by: Fanelli, Cristiano, et al.
Published: (2024)
by: Fanelli, Cristiano, et al.
Published: (2024)
COLUR: Confidence-Oriented Learning, Unlearning and Relearning with Noisy-Label Data for Model Restoration and Refinement
by: Sui, Zhihao, et al.
Published: (2025)
by: Sui, Zhihao, et al.
Published: (2025)
Closing the Gap in High-Risk Pregnancy Care Using Machine Learning and Human-AI Collaboration
by: Mozannar, Hussein, et al.
Published: (2023)
by: Mozannar, Hussein, et al.
Published: (2023)
Mapping Methane -- The Impact of Dairy Farm Practices on Emissions Through Satellite Data and Machine Learning
by: Bi, Hanqing, et al.
Published: (2024)
by: Bi, Hanqing, et al.
Published: (2024)
Sample Selection Bias in Machine Learning for Healthcare
by: Chauhan, Vinod Kumar, et al.
Published: (2024)
by: Chauhan, Vinod Kumar, et al.
Published: (2024)
A Machine Learning Approach for Emergency Detection in Medical Scenarios Using Large Language Models
by: Akaybicen, Ferit, et al.
Published: (2024)
by: Akaybicen, Ferit, et al.
Published: (2024)
How Quantization Shapes Bias in Large Language Models
by: Marcuzzi, Federico, et al.
Published: (2025)
by: Marcuzzi, Federico, et al.
Published: (2025)
Bias in Large Language Models: Origin, Evaluation, and Mitigation
by: Guo, Yufei, et al.
Published: (2024)
by: Guo, Yufei, et al.
Published: (2024)
Race, Ethnicity and Their Implication on Bias in Large Language Models
by: Hu, Shiyue, et al.
Published: (2026)
by: Hu, Shiyue, et al.
Published: (2026)
Enhancing Semi-supervised Learning with Zero-shot Pseudolabels
by: Chung, Jichan, et al.
Published: (2025)
by: Chung, Jichan, et al.
Published: (2025)
Large Language Models Reveal Information Operation Goals, Tactics, and Narrative Frames
by: Burghardt, Keith, et al.
Published: (2024)
by: Burghardt, Keith, et al.
Published: (2024)
Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models
by: Jin, Bihui, et al.
Published: (2025)
by: Jin, Bihui, et al.
Published: (2025)
GUARD: Role-playing to Generate Natural-language Jailbreakings to Test Guideline Adherence of Large Language Models
by: Jin, Haibo, et al.
Published: (2024)
by: Jin, Haibo, et al.
Published: (2024)
Structural Abstraction as an Inductive Bias for Non-Stationary Language Model Training
by: Rahmati, Elnaz, et al.
Published: (2026)
by: Rahmati, Elnaz, et al.
Published: (2026)
Integrating Machine Learning Ensembles and Large Language Models for Heart Disease Prediction Using Voting Fusion
by: Amin, Md. Tahsin, et al.
Published: (2026)
by: Amin, Md. Tahsin, et al.
Published: (2026)
Reinforcement Learning on Dyads to Enhance Medication Adherence
by: Xu, Ziping, et al.
Published: (2025)
by: Xu, Ziping, et al.
Published: (2025)
BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses
by: Xu, Xin, et al.
Published: (2025)
by: Xu, Xin, et al.
Published: (2025)
Similar Items
-
Do Sparse Autoencoders Identify Reasoning Features in Language Models?
by: Ma, George, et al.
Published: (2026) -
OC-Distill: Ontology-aware Contrastive Learning with Cross-Modal Distillation for ICU Risk Prediction
by: Liang, Zhongyuan, et al.
Published: (2026) -
ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks
by: Zhu, Yinghao, et al.
Published: (2024) -
Hybrid Meta-learners for Estimating Heterogeneous Treatment Effects
by: Liang, Zhongyuan, et al.
Published: (2025) -
Using Machine Bias To Measure Human Bias
by: Dong, Wanxue, et al.
Published: (2024)