Saved in:
| Main Authors: | Barr, Austin A., Rozman, Robert, Guo, Eddie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.14523 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Zero-shot generation of synthetic neurosurgical data with large language models
by: Barr, Austin A., et al.
Published: (2025)
by: Barr, Austin A., et al.
Published: (2025)
A comparative study of zero-shot inference with large language models and supervised modeling in breast cancer pathology classification
by: Sushil, Madhumita, et al.
Published: (2024)
by: Sushil, Madhumita, et al.
Published: (2024)
Evaluating quality in synthetic data generation for large tabular health datasets
by: Escudié, Jean-Baptiste, et al.
Published: (2026)
by: Escudié, Jean-Baptiste, et al.
Published: (2026)
AI-AI Bias: large language models favor communications generated by large language models
by: Laurito, Walter, et al.
Published: (2024)
by: Laurito, Walter, et al.
Published: (2024)
Dependency-aware synthetic tabular data generation
by: Umesh, Chaithra, et al.
Published: (2025)
by: Umesh, Chaithra, et al.
Published: (2025)
Private prediction for large-scale synthetic text generation
by: Amin, Kareem, et al.
Published: (2024)
by: Amin, Kareem, et al.
Published: (2024)
Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generation
by: Burns, Thomas F, et al.
Published: (2025)
by: Burns, Thomas F, et al.
Published: (2025)
Convex space learning for tabular synthetic data generation
by: Mahendra, Manjunath, et al.
Published: (2024)
by: Mahendra, Manjunath, et al.
Published: (2024)
Perturbation: A simple and efficient adversarial tracer for representation learning in language models
by: Rozner, Joshua, et al.
Published: (2026)
by: Rozner, Joshua, et al.
Published: (2026)
Amortizing intractable inference in large language models
by: Hu, Edward J., et al.
Published: (2023)
by: Hu, Edward J., et al.
Published: (2023)
Representation in large language models
by: Yetman, Cameron
Published: (2025)
by: Yetman, Cameron
Published: (2025)
Deep generative models as an adversarial attack strategy for tabular machine learning
by: Dyrmishi, Salijona, et al.
Published: (2024)
by: Dyrmishi, Salijona, et al.
Published: (2024)
Extracting effective solutions hidden in large language models via generated comprehensive specialists: case studies in developing electronic devices
by: Tomita, Hikari, et al.
Published: (2024)
by: Tomita, Hikari, et al.
Published: (2024)
Targeted synthetic data generation for tabular data via hardness characterization
by: Ferracci, Tommaso, et al.
Published: (2024)
by: Ferracci, Tommaso, et al.
Published: (2024)
MMM and MMMSynth: Clustering of heterogeneous tabular data, and synthetic data generation
by: Kumari, Chandrani, et al.
Published: (2023)
by: Kumari, Chandrani, et al.
Published: (2023)
Alignment faking in large language models
by: Greenblatt, Ryan, et al.
Published: (2024)
by: Greenblatt, Ryan, et al.
Published: (2024)
Lightweight reranking for language model generations
by: Jain, Siddhartha, et al.
Published: (2023)
by: Jain, Siddhartha, et al.
Published: (2023)
Explore Theory of Mind: Program-guided adversarial data generation for theory of mind reasoning
by: Sclar, Melanie, et al.
Published: (2024)
by: Sclar, Melanie, et al.
Published: (2024)
Are aligned neural networks adversarially aligned?
by: Carlini, Nicholas, et al.
Published: (2023)
by: Carlini, Nicholas, et al.
Published: (2023)
Prompt reinforcing for long-term planning of large language models
by: Lin, Hsien-Chin, et al.
Published: (2025)
by: Lin, Hsien-Chin, et al.
Published: (2025)
Machine-generated text detection prevents language model collapse
by: Drayson, George, et al.
Published: (2025)
by: Drayson, George, et al.
Published: (2025)
Long-form factuality in large language models
by: Wei, Jerry, et al.
Published: (2024)
by: Wei, Jerry, et al.
Published: (2024)
Can large language models explore in-context?
by: Krishnamurthy, Akshay, et al.
Published: (2024)
by: Krishnamurthy, Akshay, et al.
Published: (2024)
Quantifying perturbation impacts for large language models
by: Rauba, Paulius, et al.
Published: (2024)
by: Rauba, Paulius, et al.
Published: (2024)
Only relative ranks matter in weight-clustered large language models
by: Aizpurua, Borja, et al.
Published: (2026)
by: Aizpurua, Borja, et al.
Published: (2026)
Discovering influential text using convolutional neural networks
by: Ayers, Megan, et al.
Published: (2024)
by: Ayers, Megan, et al.
Published: (2024)
Question answering system of bridge design specification based on large language model
by: Zhang, Leye, et al.
Published: (2024)
by: Zhang, Leye, et al.
Published: (2024)
B-score: Detecting biases in large language models using response history
by: Vo, An, et al.
Published: (2025)
by: Vo, An, et al.
Published: (2025)
The representation landscape of few-shot learning and fine-tuning in large language models
by: Doimo, Diego, et al.
Published: (2024)
by: Doimo, Diego, et al.
Published: (2024)
Leveraging large language models for structured information extraction from pathology reports
by: Balasubramanian, Jeya Balaji, et al.
Published: (2025)
by: Balasubramanian, Jeya Balaji, et al.
Published: (2025)
ECG-LLM -- training and evaluation of domain-specific large language models for electrocardiography
by: Ahrens, Lara, et al.
Published: (2025)
by: Ahrens, Lara, et al.
Published: (2025)
DataComp-LM: In search of the next generation of training sets for language models
by: Li, Jeffrey, et al.
Published: (2024)
by: Li, Jeffrey, et al.
Published: (2024)
Can a large language model be a gaslighter?
by: Li, Wei, et al.
Published: (2024)
by: Li, Wei, et al.
Published: (2024)
Mathematics with large language models as provers and verifiers
by: Duc, Hieu Le, et al.
Published: (2025)
by: Duc, Hieu Le, et al.
Published: (2025)
CogBench: a large language model walks into a psychology lab
by: Coda-Forno, Julian, et al.
Published: (2024)
by: Coda-Forno, Julian, et al.
Published: (2024)
TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models
by: Feng, Jiarui, et al.
Published: (2024)
by: Feng, Jiarui, et al.
Published: (2024)
Scaling behavior of large language models in emotional safety classification across sizes and tasks
by: Pinzuti, Edoardo, et al.
Published: (2025)
by: Pinzuti, Edoardo, et al.
Published: (2025)
Anchor function: a type of benchmark functions for studying language models
by: Zhang, Zhongwang, et al.
Published: (2024)
by: Zhang, Zhongwang, et al.
Published: (2024)
Inducing anxiety in large language models can induce bias
by: Coda-Forno, Julian, et al.
Published: (2023)
by: Coda-Forno, Julian, et al.
Published: (2023)
Benchmarking large language models for biomedical natural language processing applications and recommendations
by: Chen, Qingyu, et al.
Published: (2023)
by: Chen, Qingyu, et al.
Published: (2023)
Similar Items
-
Zero-shot generation of synthetic neurosurgical data with large language models
by: Barr, Austin A., et al.
Published: (2025) -
A comparative study of zero-shot inference with large language models and supervised modeling in breast cancer pathology classification
by: Sushil, Madhumita, et al.
Published: (2024) -
Evaluating quality in synthetic data generation for large tabular health datasets
by: Escudié, Jean-Baptiste, et al.
Published: (2026) -
AI-AI Bias: large language models favor communications generated by large language models
by: Laurito, Walter, et al.
Published: (2024) -
Dependency-aware synthetic tabular data generation
by: Umesh, Chaithra, et al.
Published: (2025)