SciHigh 2026 Subtask 1 — Final Pipeline

Team Yushkk99. Task: generate research highlights from paper abstracts (MixSub corpus, 19,785 ScienceDirect papers). Official metric: ROUGE-L F1.

Results (validation, 1,985 rows, plain rougeL / no stemming)

system	val ROUGE-L
FIRE-2025 winning system (reference)	23.45
bart-large-cnn, original data	24.37
bart-large-cnn, repaired data + titles (run 1)	26.37
Qwen2.5-72B QLoRA, repaired data + titles (run 2)	28.33

Pipeline

Data enrichment (all sources free and sanctioned; test rows touched only via abstract/title metadata — never highlight fields):

recover_abstracts.py — ~40% of corpus abstracts are truncated mid-sentence. Each row is matched to its ScienceDirect PII (verified 100% by abstract-text join against the dataset's source repository), resolved to a DOI via Elsevier's keyless Article API, and its complete abstract fetched from Semantic Scholar. A label-free acceptance filter (recovered text must contain >=90% of the truncated text's tokens) guarantees same-paper extensions and structurally excludes records containing highlight fields. Acceptance: ~95% of truncated rows.
fetch_titles.py — paper titles for 100% of rows via the same keyless PII lookup.
build_datasets.py — rebuilds all splits with recovered abstracts normalized to the corpus's punctuation-stripped format (transform validated token-for-token against 5,481 known prefixes, mean agreement 0.987), then prepends titles: <title> | <abstract>.

Modeling:

train_qwen_qlora.py — one-epoch QLoRA SFT (4-bit NF4, LoRA r=16 on attention+MLP) of a Qwen2.5 Instruct base on the 15,960-pair titled pool, chat-formatted, greedy decoding. The identical script trains the 7B (24GB GPU) and 72B (80GB GPU) variants; only --base changes.
infer_test.py — greedy test-set inference producing the submission CSV.
validate_submission.py — format gate: row count, column schema, no empty predictions, length statistics.

Run 1 (bart lineage) reproduces via the Kaggle kernels (res-3-title-prefix) recorded in the project artifacts.

Models

Yakk99/scihigh2026-subtask1-qwen72b-qlora — run-2 adapter (72B)
Yakk99/scihigh2026-subtask1-qwen7b-qlora — 7B pilot adapter
Yakk99/scihigh2026-subtask1-bart-titled — run-1 full model

Negative results (tested and closed, full logs in project artifacts)

BRIO contrastive calibration (two decode-matched attempts, ~0 delta); MBR/DPO preference signal on the 72B pool (−2.0 — sampled candidates cluster below the greedy mode of a well-trained model); oracle bullet reordering (+0.0002); GRPO (rejected on published scientific-domain negatives); RAG (measured negative on this exact corpus by a FIRE-2025 team).