LLM errors concentrate in sparse key tokens (5-10% of sequence) at semantic decision junctions, yielding a new reliability model that explains sustained long-context coherence.
What is wrong with perplexity for long-context language modeling? InInternational Conference on Learning Representations (ICLR) 2025,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Beyond Exponential Decay: Rethinking Error Accumulation in Large Language Models
LLM errors concentrate in sparse key tokens (5-10% of sequence) at semantic decision junctions, yielding a new reliability model that explains sustained long-context coherence.