85 citations · 127 across the 6 of their papers we have counts for
4 papers · 1 filter
Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading
Howard Chen, Ramakanth Pasunuru, Jason Weston +1
Large language models (LLMs) have advanced in large strides due to the effectiveness of the self-attention mechanism that processes and compares all tokens at once. However, this m…
Shepherd: A Critic for Language Model Generation
Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan +7
As large language models improve, there is increasing interest in techniques that leverage these models' capabilities to refine their own outputs. In this work, we introduce Shephe…
OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization
Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru +15
Recent work has shown that fine-tuning large pre-trained language models on a collection of tasks described via instructions, a.k.a. instruction-tuning, improves their zero and few…
Proposition-Level Clustering for Multi-Document Summarization
Ori Ernst, Avi Caciularu, Ori Shapira +4
Text clustering methods were traditionally incorporated into multi-document summarization (MDS) as a means for coping with considerable information repetition. Particularly, cluste…