22 citations · 40 across the 9 of their papers we have counts for
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cs.CL2024
Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries
Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni +21
We introduce Michelangelo: a minimal, synthetic, and unleaked long-context reasoning evaluation for large language models which is also easy to automatically score. This evaluation…
cs.LG2024★ 1 cited
Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles
Kulin Shah, Nishanth Dikkala, Xin Wang +1
Causal language modeling using the Transformer architecture has yielded remarkable capabilities in Large Language Models (LLMs) over the last few years. However, the extent to whic…