most citedTesting the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks

1 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024★ 1 cited

Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning

Soumajyoti Sarkar, Leonard Lausen, Volkan Cevher +3

Sparse Mixture of Expert (SMoE) models have emerged as a scalable alternative to dense models in language modeling. These models use conditionally activated feedforward subnetworks…

cs.LG2024

EMC: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence

Chung-Yiu Yau, Hoi-To Wai, Parameswaran Raman +2

A key challenge in contrastive learning is to generate negative samples from a large sample set to contrast with positive samples, for learning better encoding of the data. These n…

cs.CL2023★ 1 cited

Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks

Soumajyoti Sarkar, Leonard Lausen

Tables stored in databases and tables which are present in web pages and articles account for a large part of semi-structured data that is available on the internet. It then become…