Search Results for author:
Found 9 papers, 5 papers with code
TRAM: Bridging Trust Regions and Sharpness Aware Minimization
We propose Trust Region Aware Minimization (TRAM), a SAM algorithm fine-tuning for low parameter sharpness and smooth, informative representations preserving pre-trained structure.
Efficiency Pentathlon: A Standardized Arena for Efficiency Evaluation
In response, we introduce Pentathlon, a benchmark for holistic and realistic evaluation of model efficiency.
Optimal Transport Posterior Alignment for Cross-lingual Semantic Parsing
Cross-lingual semantic parsing transfers parsing capability from a high-resource language (e. g., English) to low-resource languages with scarce training data.
How To Train Your (Compressed) Large Language Model
With the increase in the size of large language models (LLMs), we need compression methods that can reduce the model size while preserving the generality and zero-shot promptability of the model.
Extrinsic Evaluation of Machine Translation Metrics
We calculate the correlation between the metric's ability to predict a good/bad translation with the success/failure on the final task for the Translate-Test setup.
Meta-Learning a Cross-lingual Manifold for Semantic Parsing
We introduce a first-order meta-learning algorithm to train a semantic parser with maximal sample efficiency during cross-lingual transfer.
Zero-Shot Cross-lingual Semantic Parsing
Recent work in cross-lingual semantic parsing has successfully applied machine translation to localize parsers to new languages.
Bootstrapping a Crosslingual Semantic Parser
Considering when MT is inadequate, we also find that using our approach achieves parsing accuracy within 2% of complete translation using only 50% of training data.
Going Beneath the Surface: Evaluating Image Captioning for Grammaticality, Truthfulness and Diversity
Image captioning as a multimodal task has drawn much interest in recent years.
