RepCNN: Micro-Sized, Mighty Models for Wakeword Detection
Always-on machine learning models require a very low memory and compute footprint. Their restricted parameter count limits the model’s capacity to learn, and...
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2024
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2024
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ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities
Recent large language models (LLMs) advancements sparked a growing research interest in tool assisted LLMs solving real-world challenges, which calls for comprehensive evaluation...
KGLens: Towards Efficient and Effective Knowledge Probing of Large Language Models with Knowledge Graphs
This paper was accepted at the Workshop Towards Knowledgeable Language Models 2024.
Large Language Models (LLMs) might hallucinate facts, while curated Knowledge Graph (KGs)...
ACL Conference 2024
Apple is sponsoring the annual meeting of the Association for Computational Linguistics (ACL), which takes place in person from August 11 to 16,...
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...
