Publications

Forging Time Series with Language: A Large Language Model Approach to Synthetic Data Generation
- - Cécile Rousseau
  - Tobia Boschi
  - et al.
- 2025
- NeurIPS 2025
Conference paper
Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve
- - Yuanzhe Liu
  - Ryan Deng
  - et al.
- 2025
- NeurIPS 2025
Conference paper
Analog Foundation Models
- - Julian Büchel
  - Iason Chalas
  - et al.
- 2025
- NeurIPS 2025
Conference paper
Optimality and NP-Hardness of Transformers in Learning Markovian Dynamical Functions
- - Yanna Ding
  - Songtao Lu
  - et al.
- 2025
- NeurIPS 2025
Conference paper
Fair Continuous Resource Allocation with Equality of Impact
- - Blossom Metevier
  - Dennis Wei
  - et al.
- 2025
- NeurIPS 2025
Conference paper
RCCDA: Adaptive Model Updates in the Presence of Concept Drift under a Constrained Resource Budget
- - Adam Piaseczny
  - Kamran Shisher
  - et al.
- 2025
- NeurIPS 2025
Conference paper
CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
- - Chen Xiong
  - Pin-Yu Chen
  - et al.
- 2025
- NeurIPS 2025
Conference paper
Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts
- - Andrea Pugnana
  - Riccardo Massidda
  - et al.
- 2025
- NeurIPS 2025
Conference paper
BenchmarkCards: Standardized Documentation for Large Language Model Benchmarks
- - Anna Sokol
  - Elizabeth Daly
  - et al.
- 2025
- NeurIPS 2025
Conference paper
Optimal Estimation of the Best Mean in Multi-Armed Bandits
- - Takayuki Osogami
  - Junya Honda
  - et al.
- 2025
- NeurIPS 2025
Conference paper