30 citations · 36 across the 6 of their papers we have counts for
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cs.CL2026
RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably
Yufeng Du, Phillip Harris, Minyang Tian +5
We identify intrinsic limitations of Rotary Positional Embeddings (RoPE) in Transformer-based long-context language models. Our theoretical analysis abstracts away from the specifi…
cs.CL2025★ 3 cited
Context Length Alone Hurts LLM Performance Despite Perfect Retrieval
Yufeng Du, Minyang Tian, Srikanth Ronanki +7
Large language models (LLMs) often fail to scale their performance on long-context tasks performance in line with the context lengths they support. This gap is commonly attributed…