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Note no anchor recorded: the extractor captured no citation for this entry, and the citing paper's reference entry was never read. The paper does cite it, so this is a gap in our extraction rather than in the source Findings IC-034 Benefit and detriment in RAG can be traded off at token level for Llama-2, OPT and Mistral using representation similarity [eval] IC-043 Five ~7B decoder-only LLMs develop a high-intrinsic-dimensionality phase in intermediate layers that marks the transition from surface-form to abstract linguistic processing, with earlier onset predicting better next-token prediction [eval] IC-1151 LLaMA, OPT, LLaMA-2, Mistral, and GPT-J all exhibit token co-occurrence reinforcement, where the probability of generating a token increases monotonically with the number of its contextual co-occurrences [eval] IC-575 Four released LLMs (LLaMA-3.1-8B, Mistral-7B, Qwen2-7B, Yi-1.5-9B) can perform in-context learning on continuous vector representations projected into their embedding space, matching or outperforming few-shot ICL across text, time-series, graph, and fMRI tasks [train] IC-913 In OPT-2.7B, Pythia-70M/1.4B/6.9B, and BERT-base, the stable rank of MLP lower layers shows a drop-and-bounce pattern during training that is more salient in top layers while bottom layers show suppressed dropping curves [eval]