Spaces:
Running
Running
| { | |
| "schema_version": 1, | |
| "title": "Reproduction: Generalization and Forgetting in In-Context Continual Learning", | |
| "emoji": "🧠", | |
| "space_id": "snaykey/repro-incontext-cl", | |
| "paper": { | |
| "openreview_id": "68AMoK2YNk" | |
| }, | |
| "tags": [ | |
| "icml2026-repro", | |
| "paper-68AMoK2YNk" | |
| ], | |
| "updated_at": "2026-08-02T00:00:00+00:00", | |
| "root": { | |
| "slug": "index", | |
| "title": "Reproduction: Generalization and Forgetting in In-Context Continual Learning", | |
| "file": "pages/index.md", | |
| "children": [ | |
| { | |
| "slug": "claim-1-thm43-decomposition", | |
| "title": "Theorem 4.3 decomposes the task-t prediction error into an irreducible error term, a variance term scaling as O(M/(t^2(M+1)^2)) that decreases with more in-context examples, and a bias term measuring deviation ‖(1/t)∑_s w_s - w_t‖^2 from task dissimilarity (Theorem 4.3).", | |
| "file": "pages/claim-1-thm43-decomposition/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-2-thm44-reweighting", | |
| "title": "Theorem 4.4 shows that forgetting arises from attention reweighting past tasks with negative coefficients c_t and future tasks with positive coefficients d, rather than from actual information loss, comprising intra-task variance and inter-task mean-interaction terms (Theorem 4.4).", | |
| "file": "pages/claim-2-thm44-reweighting/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-3-nonmonotonic-peak", | |
| "title": "The theory predicts non-monotonic error curves with context length M, where longer prompts reduce variance but amplify systematic bias from misaligned historical tasks, producing a clear performance peak at intermediate M (Section 4, theoretical analysis).", | |
| "file": "pages/claim-3-nonmonotonic-peak/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-4-forgetting-floor", | |
| "title": "Mean-misalignment interference persists regardless of context length, while variance-induced interference decays as O(1/M), implying a persistent asymptotic forgetting floor (Section 4, theoretical analysis).", | |
| "file": "pages/claim-4-forgetting-floor/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-5-gpt2-validation", | |
| "title": "Experiments on GPT-2 architectures confirm the predicted non-monotonic error curves and reproduce catastrophic forgetting with a 46% accuracy drop on real LLM tasks (Section 5, experimental validation).", | |
| "file": "pages/claim-5-gpt2-validation/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "executive-summary", | |
| "title": "executive-summary", | |
| "file": "pages/executive-summary/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "conclusion", | |
| "title": "conclusion", | |
| "file": "pages/conclusion/page.md", | |
| "children": [] | |
| } | |
| ] | |
| } | |
| } |