4 citations · 5 across the 2 of their papers we have counts for
3 papers
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study
Menglong Cui, Pengzhi Gao, Wei Liu +2
Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…
MLGym: A New Framework and Benchmark for Advancing AI Research Agents
Deepak Nathani, Lovish Madaan, Nicholas Roberts +14
We introduce Meta MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. This is the first Gym environment for machine…
Logic.py: Bridging the Gap between LLMs and Constraint Solvers
Pascal Kesseli, Peter O'Hearn, Ricardo Silveira Cabral
We present a novel approach to formalise and solve search-based problems using large language models, which significantly improves upon previous state-of-the-art results. We demons…