Leshem Choshen

Publications

• Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability

  • • Afra Feyza Akyürek
    • Ekin Akyürek
    • et al.
  • 2024
  • ACL 2024

• Data Contamination Report from the 2024 CONDA Shared Task

  • • Oscar Sainz
    • Iker García-ferrero
    • et al.
  • 2024
  • ACL 2024

• tinyBenchmarks: evaluating LLMs with fewer examples

  • • Felipe Maia Polo
    • Lucas Weber
    • et al.
  • 2024
  • ICML 2024

• Asymmetry in Low-Rank Adapters of Foundation Models

  • • Jiacheng Zhu
    • Kristjan Greenewald
    • et al.
  • 2024
  • ICML 2024

• Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI

  • • Elron Bandel
    • Yotam Perlitz
    • et al.
  • 2024
  • NAACL 2024

• Navigating the Modern Evaluation Landscape: Considerations in Benchmarks and Frameworks for Large Language Models (LLMs)

  • • Leshem Choshen
    • Ariel Gera
    • et al.
  • 2024
  • LREC-COLING 2024

• ACHIEVING HUMAN PARITY IN CONTENT-GROUNDED DATASETS GENERATION

  • • Asaf Yehudai
    • Boaz Carmeli
    • et al.
  • 2024
  • ICLR 2024

• Asymmetry in Low-Rank Adapters of Foundation Models

  • • Jiacheng Zhu
    • Kristjan Greenewald
    • et al.
  • 2024
  • ICLR 2024

• tinyBenchmarks: evaluating LLMs with fewer examples

  • • Felipe Maia Polo
    • Lucas Weber
    • et al.
  • 2024
  • ICLR 2024

• TIES-Merging: Resolving Interference When Merging Models

  • • Prateek Yadav
    • Derek Tam
    • et al.
  • 2023
  • NeurIPS 2023