ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA Datasets with Large Language Models
The rapid evolution of Large Language Models (LLMs) and conversational assistants necessitates dynamic, scalable, and configurable conversational datasets for training and evaluation. These...
LLM in a Flash: Efficient Large Language Model Inference with Limited Memory
This paper was accepted at the ACL 2024
Large language models (LLMs) are central to modern natural language processing, delivering exceptional performance in various...
Generating Gender Alternatives in Machine Translation
This paper was accepted at the 5th Workshop on Gender Bias in Natural Language Processing 2024.
Machine translation (MT) systems often translate terms with...
Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation
Aligning large language models (LLMs) with human expectations without human-annotated preference data is an important problem. In this paper, we propose a method...
BISCUIT: Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebooks
This paper was accepted at IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) 2024
Programmers frequently engage with machine learning tutorials in computational...
Tuning LLMs with Contrastive Alignment Instructions for Machine Translation in Unseen, Low-resource Languages
This article introduces contrastive alignment instructions (AlignInstruct) to address two challenges in machine translation (MT) on large language models (LLMs). One is the...
LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference
This paper was accepted at the Efficient Systems for Foundation Models Workshop at ICML 2024
The inference of transformer-based large language models consists of...
Model-Driven Heart Rate Estimation and Heart Murmur Detection Based on Phonocardiogram
Acoustic signals are crucial for health monitoring, particularly heart sounds which provide essential data like heart rate and detect cardiac anomalies such as...
DataComp-LM: In Search of the Next Generation of Training Sets for Language Models
This paper was accepted at the NeurIPS Datasets and Benchmarks Workshop at NeurIPS 2024
We introduce DataComp for Language Models (DCLM), a testbed for...
Instance Optimal Private Density Estimation in the Wasserstein Distance
Estimating the density of a distribution from samples is a fundamental problem in statistics. In many practical settings, the Wasserstein distance is an...
