Search Results for author:
Found 8 papers, 3 papers with code
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
The challenge is that information entropy may be a suboptimal compression metric: (i) it only leverages unidirectional context and may fail to capture all essential information needed for prompt compression; (ii) it is not aligned with the prompt compression objective.
Unlocking Spatial Comprehension in Text-to-Image Diffusion Models
We propose CompFuser, an image generation pipeline that enhances spatial comprehension and attribute assignment in text-to-image generative models.
Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective
In this paper, we take an information flow control perspective to describe machine learning systems, which allows us to leverage metadata such as access control policies and define clear-cut privacy and confidentiality guarantees with interpretable information flows.
Hybrid Retrieval-Augmented Generation for Real-time Composition Assistance
Retrieval augmentation enhances performance of traditional language models by incorporating additional context.
Multilingual Neural Semantic Parsing for Low-Resourced Languages
To evaluate our multilingual models on human-written sentences as opposed to machine translated ones, we introduce a new multilingual semantic parsing dataset in English, Italian and Japanese based on the Facebook Task Oriented Parsing (TOP) dataset.
Generating Semantically Valid Adversarial Questions for TableQA
Finally, we demonstrate that adversarial training with SAGE augmented data can improve performance and robustness of TableQA systems.
Text Readability Assessment for Second Language Learners
This paper addresses the task of readability assessment for the texts aimed at second language (L2) learners.
Automatic learner summary assessment for reading comprehension
Automating the assessment of learner summaries provides a useful tool for assessing learner reading comprehension.
