In-Context Retrieval-Augmented Language Models (2023 · 793 citations)
Language models often fabricate facts and do not indicate where they obtained their information. Retrieval-augmented approaches that draw on external documents (RALM) mitigate this problem. However, known solutions such as RETRO modify the model architecture and require additional training, so they are rarely used in…
Generating Benchmarks for Factuality Evaluation of Language Models (2024 · 81 citations)
Measuring how often a language model produces false statements in a given domain is hard. Methods that fact-check a model's own samples cannot choose which facts get tested, and they favour common knowledge over rare or domain-specific facts. Perplexity is often used as a stand-in, but it reflects many linguistic…
Jamba-1.5: Hybrid Transformer-Mamba Models at Scale (2024 · 30 citations)
Long contexts make standard Transformer LLMs costly to serve because the KV cache grows quickly and slows inference.

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