UNVEILING THE SECRET RECIPE: A GUIDE FOR SUPERVISED FINE-TUNING SMALL LLMS
- Aldo Pareja
- Nikhil Shivakumar Nayak
- et al.
- 2025
- ICLR 2025
Conference paper
Publications
9 results for Akash Srivastava
SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models
- Xinxi Zhang
- Song Wen
- et al.
- 2025
- WACV 2025
Conference paperBeyond Statistical Similarity: Rethinking Metrics for Deep Generative Models in Engineering Design
- Lyle Regenwetter
- Akash Srivastava
- et al.
- 2023
- Computer-Aided Design
PaperMulti-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries
- Charlotte Loh
- Seungwook Han
- et al.
- 2023
- ICML 2023
Conference paperLINKS: A DATASET OF A HUNDRED MILLION PLANAR LINKAGE MECHANISMS FOR DATA-DRIVEN KINEMATIC DESIGN
- Amin Heyrani Nobari
- Akash Srivastava
- et al.
- 2022
- IDETC-CIE 2022
Conference paperEQUIVARIANT CONTRASTIVE LEARNING
- Rumen Dangovski
- Li Jing
- et al.
- 2022
- ICLR 2022
Conference paperSequential transfer machine learning in networks: Measuring the impact of data and neural net similarity on transferability
- Robin Hirt
- Akash Srivastava
- et al.
- 2021
- HICSS 2021
Conference paperScalable spike source localization in extracellular recordings using amortized variational inference
- Cole L. Hurwitz
- Kai Xu
- et al.
- 2019
- NeurIPS 2019
Conference paperVariational Russian roulette for deep Bayesian nonparametrics
- Kai Xu
- Akash Srivastava
- et al.
- 2019
- ICML 2019
Conference paper