Search papers, labs, and topics across Lattice.
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Explicitly enumerating skills in-context doesn't scale for agentic LLMs, but retrieving skills on demand can substantially improve performance – if the LLM can figure out when and which skill to load.
Meta's new hierarchical indexing method lets you deploy massive recommendation models without sacrificing speed or accuracy, and it turns out the index itself highlights a high-quality subset of data perfect for test-time training.
Current search paradigms fall short for analytical tasks, motivating a new "analytical search" framework that treats search as an evidence-driven, multi-step reasoning process.
LLMs still can't convincingly mimic human personas, especially when it comes to syntactic style and memory, despite advancements in other areas.
LLMs still struggle to learn effectively from user feedback during service, as revealed by a new benchmark spanning multiple domains and languages.
