4 citations · 8 across the 22 of their papers we have counts for
Showing 2024 · cs.CLShow all
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cs.CL2024★ 1 cited
Understanding Synthetic Context Extension via Retrieval Heads
Xinyu Zhao, Fangcong Yin, Greg Durrett
Long-context LLMs are increasingly in demand for applications such as retrieval-augmented generation. To defray the cost of pretraining LLMs over long contexts, recent work takes a…
cs.CL2024★ 4 cited
Molecular Facts: Desiderata for Decontextualization in LLM Fact Verification
Anisha Gunjal, Greg Durrett
Automatic factuality verification of large language model (LLM) generations is becoming more and more widely used to combat hallucinations. A major point of tension in the literatu…
cs.CL2024★ 1 cited
SynthesizRR: Generating Diverse Datasets with Retrieval Augmentation
Abhishek Divekar, Greg Durrett
It is often desirable to distill the capabilities of large language models (LLMs) into smaller student models due to compute and memory constraints. One way to do this for classifi…