finding
active
finding:logit-based-self-report-achieves-3-1-3-7-bits-entropy-vs-0-03-1-10-bits-greedy-and-0-68-2-05-bits-sampled-in-llama-3-2-3b

Logit-based self-report achieves 3.1–3.7 bits entropy vs 0.03–1.10 bits greedy and 0.68–2.05 bits sampled in LLaMA-3.2-3B

Quantifies the information gain from using logit-based expected value over greedy or sampled decoding

Source paper

extracted_from
Quantitative Introspection in Language Models: Tracking Emotive States Across Conversation
(2026) · Nicolas Martorell · Bianchi, Bruno

Neighborhood — ranked by edge-count

Claims (1)

claim

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.