Fill In The Gaps: Model Calibration and Generalization with Synthetic Data
Fuente:
arXiv
Saved in:
| Main Authors: | Ba, Yang, Mancenido, Michelle V., Pan, Rong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Data Diversity as Implicit Regularization: How Does Diversity Shape the Weight Space of Deep Neural Networks?
by: Ba, Yang, et al.
Published: (2024)
by: Ba, Yang, et al.
Published: (2024)
Data Quality in Crowdsourcing and Spamming Behavior Detection
by: Ba, Yang, et al.
Published: (2024)
by: Ba, Yang, et al.
Published: (2024)
FutureFill: Fast Generation from Convolutional Sequence Models
by: Agarwal, Naman, et al.
Published: (2024)
by: Agarwal, Naman, et al.
Published: (2024)
CALICO: Conversational Agent Localization via Synthetic Data Generation
by: Rosenbaum, Andy, et al.
Published: (2024)
by: Rosenbaum, Andy, et al.
Published: (2024)
SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging
by: Pourreza, Mohammadreza, et al.
Published: (2024)
by: Pourreza, Mohammadreza, et al.
Published: (2024)
Beware of Calibration Data for Pruning Large Language Models
by: Ji, Yixin, et al.
Published: (2024)
by: Ji, Yixin, et al.
Published: (2024)
Contrastive Decoding for Synthetic Data Generation in Low-Resource Language Modeling
by: Ulm, Jannek, et al.
Published: (2025)
by: Ulm, Jannek, et al.
Published: (2025)
Reasoning-Driven Synthetic Data Generation and Evaluation
by: Davidson, Tim R., et al.
Published: (2026)
by: Davidson, Tim R., et al.
Published: (2026)
DiffLM: Controllable Synthetic Data Generation via Diffusion Language Models
by: Zhou, Ying, et al.
Published: (2024)
by: Zhou, Ying, et al.
Published: (2024)
Enhancing Clinical Documentation with Synthetic Data: Leveraging Generative Models for Improved Accuracy
by: Biswas, Anjanava, et al.
Published: (2024)
by: Biswas, Anjanava, et al.
Published: (2024)
BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation
by: Zhu, Alan, et al.
Published: (2025)
by: Zhu, Alan, et al.
Published: (2025)
Out-of-Distribution Detection using Synthetic Data Generation
by: Abbas, Momin, et al.
Published: (2025)
by: Abbas, Momin, et al.
Published: (2025)
Dynamic Context Evolution for Scalable Synthetic Data Generation
by: Lingo, Ryan, et al.
Published: (2026)
by: Lingo, Ryan, et al.
Published: (2026)
CasualSynth: Generating Structurally Sound Synthetic Data
by: Cheng, Zehua, et al.
Published: (2026)
by: Cheng, Zehua, et al.
Published: (2026)
Enhancing Domain-Specific Retrieval-Augmented Generation: Synthetic Data Generation and Evaluation using Reasoning Models
by: Jadon, Aryan, et al.
Published: (2025)
by: Jadon, Aryan, et al.
Published: (2025)
Enabling Autoregressive Models to Fill In Masked Tokens
by: Israel, Daniel, et al.
Published: (2025)
by: Israel, Daniel, et al.
Published: (2025)
Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models
by: Yang, Zihua, et al.
Published: (2026)
by: Yang, Zihua, et al.
Published: (2026)
Matrix: Peer-to-Peer Multi-Agent Synthetic Data Generation Framework
by: Wang, Dong, et al.
Published: (2025)
by: Wang, Dong, et al.
Published: (2025)
A Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated by Large Language Models
by: Yuan, Yefeng, et al.
Published: (2024)
by: Yuan, Yefeng, et al.
Published: (2024)
Socially Aware Synthetic Data Generation for Suicidal Ideation Detection Using Large Language Models
by: Ghanadian, Hamideh, et al.
Published: (2024)
by: Ghanadian, Hamideh, et al.
Published: (2024)
Calibrating Large Language Models Using Their Generations Only
by: Ulmer, Dennis, et al.
Published: (2024)
by: Ulmer, Dennis, et al.
Published: (2024)
Alignment through Meta-Weighted Online Sampling: Bridging the Gap between Data Generation and Preference Optimization
by: Yang, Junming, et al.
Published: (2025)
by: Yang, Junming, et al.
Published: (2025)
Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use
by: Goldie, Anna, et al.
Published: (2025)
by: Goldie, Anna, et al.
Published: (2025)
CodecLM: Aligning Language Models with Tailored Synthetic Data
by: Wang, Zifeng, et al.
Published: (2024)
by: Wang, Zifeng, et al.
Published: (2024)
Does Training on Synthetic Data Make Models Less Robust?
by: Zhang, Lingze, et al.
Published: (2025)
by: Zhang, Lingze, et al.
Published: (2025)
Calibrating Long-form Generations from Large Language Models
by: Huang, Yukun, et al.
Published: (2024)
by: Huang, Yukun, et al.
Published: (2024)
Building a Foundational Guardrail for General Agentic Systems via Synthetic Data
by: Huang, Yue, et al.
Published: (2025)
by: Huang, Yue, et al.
Published: (2025)
Synthetic vs. Gold: The Role of LLM Generated Labels and Data in Cyberbullying Detection
by: Kazemi, Arefeh, et al.
Published: (2025)
by: Kazemi, Arefeh, et al.
Published: (2025)
DualAlign: Generating Clinically Grounded Synthetic Data
by: Li, Rumeng, et al.
Published: (2025)
by: Li, Rumeng, et al.
Published: (2025)
Gap-K%: Measuring Top-1 Prediction Gap for Detecting Pretraining Data
by: Kwak, Minseo, et al.
Published: (2026)
by: Kwak, Minseo, et al.
Published: (2026)
XL-Suite: Cross-Lingual Synthetic Training and Evaluation Data for Open-Ended Generation
by: Iyer, Vivek, et al.
Published: (2025)
by: Iyer, Vivek, et al.
Published: (2025)
MetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generation
by: Riaz, Haris, et al.
Published: (2025)
by: Riaz, Haris, et al.
Published: (2025)
Synthetic Multimodal Question Generation
by: Wu, Ian, et al.
Published: (2024)
by: Wu, Ian, et al.
Published: (2024)
Memorization Dynamics of Fill-in-the-Middle Pretraining
by: von Arx, Tobias, et al.
Published: (2026)
by: von Arx, Tobias, et al.
Published: (2026)
Synthetic Data for any Differentiable Target
by: Thrush, Tristan, et al.
Published: (2026)
by: Thrush, Tristan, et al.
Published: (2026)
Linguistic Calibration of Long-Form Generations
by: Band, Neil, et al.
Published: (2024)
by: Band, Neil, et al.
Published: (2024)
Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual Classification
by: Pecher, Branislav, et al.
Published: (2026)
by: Pecher, Branislav, et al.
Published: (2026)
On the Entropy Calibration of Language Models
by: Cao, Steven, et al.
Published: (2025)
by: Cao, Steven, et al.
Published: (2025)
SYN-DIGITS: A Synthetic Control Framework for Calibrated Digital Twin Simulation
by: Fan, Grace Jiarui, et al.
Published: (2026)
by: Fan, Grace Jiarui, et al.
Published: (2026)
Not All Synthetic Data Is Yours to Learn From
by: Alemohammad, Sina, et al.
Published: (2026)
by: Alemohammad, Sina, et al.
Published: (2026)
Similar Items
-
Data Diversity as Implicit Regularization: How Does Diversity Shape the Weight Space of Deep Neural Networks?
by: Ba, Yang, et al.
Published: (2024) -
Data Quality in Crowdsourcing and Spamming Behavior Detection
by: Ba, Yang, et al.
Published: (2024) -
FutureFill: Fast Generation from Convolutional Sequence Models
by: Agarwal, Naman, et al.
Published: (2024) -
CALICO: Conversational Agent Localization via Synthetic Data Generation
by: Rosenbaum, Andy, et al.
Published: (2024) -
SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging
by: Pourreza, Mohammadreza, et al.
Published: (2024)