{ "schema_version": 1, "title": "Reproduction: Training–Inference Consistent Segmented Execution for Long-Context LLMs", "emoji": "🎯", "space_id": "Umong/repro-training-inference-consistent-segmented-execution-for-long-context-llms", "paper": { "arxiv_id": "2605.11744" }, "tags": [ "icml2026-repro", "paper-PoRigyDOcC" ], "updated_at": "2026-07-18T18:43:55+00:00", "root": { "slug": "index", "title": "Reproduction: Training–Inference Consistent Segmented Execution for Long-Context LLMs", "file": "pages/index.md", "children": [ { "slug": "executive-summary", "title": "Executive summary", "file": "pages/executive-summary/page.md", "children": [] }, { "slug": "claim-1-the-framework-defines-segment-level-execution-semantics-where-training-and-inference-process-sequences-segment-by-segment-with-the-same-cross-segment-interface-definition-3-1", "title": "Claim 1: The framework defines segment-level execution semantics where training and inference process sequences segment by segment with the same cross-segment interface (Definition 3.1)", "file": "pages/claim-1-the-framework-defines-segment-level-execution-semantics-where-training-and-inference-process-sequences-segment-by-segment-with-the-same-cross-segment-interface-definition-3-1/page.md", "children": [] }, { "slug": "claim-2-for-the-stated-truncated-consistent-objective-tbptt-computes-the-exact-gradient-rather-than-an-approximation-theorem-3-3", "title": "Claim 2: For the stated truncated consistent objective, TBPTT computes the exact gradient rather than an approximation (Theorem 3.3)", "file": "pages/claim-2-for-the-stated-truncated-consistent-objective-tbptt-computes-the-exact-gradient-rather-than-an-approximation-theorem-3-3/page.md", "children": [] }, { "slug": "claim-3-training-inference-alignment-follows-when-the-same-segmented-execution-semantics-and-truncated-objective-are-used-for-training-and-inference-corollary-3-4", "title": "Claim 3: Training-inference alignment follows when the same segmented execution semantics and truncated objective are used for training and inference (Corollary 3.4)", "file": "pages/claim-3-training-inference-alignment-follows-when-the-same-segmented-execution-semantics-and-truncated-objective-are-used-for-training-and-inference-corollary-3-4/page.md", "children": [] }, { "slug": "claim-4-the-architecture-uses-head-and-layer-sparse-long-range-retrieval-with-carried-kv-tails-and-forward-only-retrieved-prefixes-figure-3", "title": "Claim 4: The architecture uses head- and layer-sparse long-range retrieval with carried KV tails and forward-only retrieved prefixes (Figure 3)", "file": "pages/claim-4-the-architecture-uses-head-and-layer-sparse-long-range-retrieval-with-carried-kv-tails-and-forward-only-retrieved-prefixes-figure-3/page.md", "children": [] }, { "slug": "claim-5-the-method-achieves-comparable-longbench-e-performance-while-lowering-prefill-memory-and-latency-relative-to-full-context-attention-and-other-efficient-baselines-table-1", "title": "Claim 5: The method achieves comparable LongBench-E performance while lowering prefill memory and latency relative to full-context attention and other efficient baselines (Table 1)", "file": "pages/claim-5-the-method-achieves-comparable-longbench-e-performance-while-lowering-prefill-memory-and-latency-relative-to-full-context-attention-and-other-efficient-baselines-table-1/page.md", "children": [] }, { "slug": "claim-6-at-128k-context-segmented-execution-provides-approximately-6x-lower-peak-prefill-memory-than-full-context-attention-with-flashattention-figure-5", "title": "Claim 6: At 128K context, segmented execution provides approximately 6x lower peak prefill memory than full-context attention with FlashAttention (Figure 5)", "file": "pages/claim-6-at-128k-context-segmented-execution-provides-approximately-6x-lower-peak-prefill-memory-than-full-context-attention-with-flashattention-figure-5/page.md", "children": [] }, { "slug": "conclusion", "title": "Conclusion", "file": "pages/conclusion/page.md", "children": [] } ] }, "agent_view_tokens": 4151, "revision": "1784400235352425480" }