Publications

tinyBenchmarks: evaluating LLMs with fewer examples
- - Felipe Maia Polo
  - Lucas Weber
  - et al.
- 2024
- ICML 2024
Trust Regions for Explanations via Black-Box Probabilistic Certification
- - Amit Dhurandhar
  - Swagatam Haldar
  - et al.
- 2024
- ICML 2024
Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series
- - Asterios Tsiourvas
  - Wei Sun
  - et al.
- 2024
- ICML 2024
Quantum Theory and Application of Contextual Optimal Transport
- - Nicola Mariella
  - Albert Akhriev
  - et al.
- 2024
- ICML 2024
Asymmetry in Low-Rank Adapters of Foundation Models
- - Jiacheng Zhu
  - Kristjan Greenewald
  - et al.
- 2024
- ICML 2024
Risk Aware Benchmarking of Large Language Models
- - Apoorva Nitsure
  - Youssef Mroueh
  - et al.
- 2024
- ICML 2024
Thermometer: Towards Universal Calibration for Large Language Models
- - Maohao Shen
  - Subhro Das
  - et al.
- 2024
- ICML 2024
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
- - Hongkang Li
  - Meng Weng
  - et al.
- 2024
- ICML 2024
Representing Molecules as Random Walks Over Interpretable Grammars
- - Michael Sun
  - Minghao Guo
  - et al.
- 2024
- ICML 2024
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts
- - Mohammed Nowaz Rabbani Chowdhury
  - Meng Wang
  - et al.
- 2024
- ICML 2024