8 citations · 17 across the 7 of their papers we have counts for
7 papers
Scalable Model-Based Clustering with Sequential Monte Carlo
Connie Trojan, Pavel Myshkov, Paul Fearnhead +3
In online clustering problems, there is often a large amount of uncertainty over possible cluster assignments that cannot be resolved until more data are observed. This difficulty…
Pyramid Vector Quantization for LLMs
Tycho F. A. van der Ouderaa, Maximilian L. Croci, Agrin Hilmkil +1
Recent works on compression of large language models (LLM) using quantization considered reparameterizing the architecture such that weights are distributed on the sphere. This dem…
KBLaM: Knowledge Base augmented Language Model
Xi Wang, Taketomo Isazawa, Liana Mikaelyan +1
In this paper, we propose Knowledge Base augmented Language Model (KBLaM), a new method for augmenting Large Language Models (LLMs) with external knowledge. KBLaM works with a know…
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci +6
We introduce QuaRot, a new Quantization scheme based on Rotations, which is able to quantize LLMs end-to-end, including all weights, activations, and KV cache in 4 bits. QuaRot rot…
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento +2
Large language models have become the cornerstone of natural language processing, but their use comes with substantial costs in terms of compute and memory resources. Sparsificatio…
Learning to Extract Structured Entities Using Language Models
Haolun Wu, Ye Yuan, Liana Mikaelyan +4
Recent advances in machine learning have significantly impacted the field of information extraction, with Language Models (LMs) playing a pivotal role in extracting structured info…
DiSK: A Diffusion Model for Structured Knowledge
Ouail Kitouni, Niklas Nolte, James Hensman +1
Structured (dictionary-like) data presents challenges for left-to-right language models, as they can struggle with structured entities for a wide variety of reasons such as formatt…