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@@ -49,50 +49,36 @@ configs:
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  data_files:
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  - split: full
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  path: hackersignal_sample_10k.jsonl
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- - config_name: task1_exploit_clf
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  data_files:
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  - split: train
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- path: benchmark/task1_exploit_clf/train.jsonl
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  - split: validation
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- path: benchmark/task1_exploit_clf/val.jsonl
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  - split: test
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- path: benchmark/task1_exploit_clf/test.jsonl
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- - config_name: task2_cve_linkage
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- data_files:
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- - split: train
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- path: benchmark/task2_cve_linkage/train.jsonl
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- - split: validation
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- path: benchmark/task2_cve_linkage/val.jsonl
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- - split: test
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- path: benchmark/task2_cve_linkage/test.jsonl
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  - split: corpus
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- path: benchmark/task2_cve_linkage/corpus.jsonl
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- - config_name: task3_severity
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- data_files:
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- - split: train
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- path: benchmark/task3_severity/train.jsonl
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- - split: validation
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- path: benchmark/task3_severity/val.jsonl
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- - split: test
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- path: benchmark/task3_severity/test.jsonl
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- - config_name: task4_hacker_exploit_labeling
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  data_files:
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  - split: train
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- path: benchmark/task4_hacker_exploit_labeling/train.jsonl
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  - split: validation
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- path: benchmark/task4_hacker_exploit_labeling/val.jsonl
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  - split: test
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- path: benchmark/task4_hacker_exploit_labeling/test.jsonl
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- - config_name: task5_hacker_signal_detection
 
 
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  data_files:
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  - split: train
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- path: benchmark/task5_hacker_signal_detection/train.jsonl
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  - split: validation
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- path: benchmark/task5_hacker_signal_detection/val.jsonl
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  - split: test
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- path: benchmark/task5_hacker_signal_detection/test.jsonl
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  - split: corpus
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- path: benchmark/task5_hacker_signal_detection/corpus.jsonl
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  ---
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  # HackerSignal
@@ -108,7 +94,7 @@ A large-scale, multi-source dataset linking hacker community discourse, exploit
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  | Source layers | 8 |
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  | Temporal span | 1988--2026 |
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  | CVE-linked rows | 360,004 |
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- | Benchmark tasks | 5 |
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  ## Quick Start
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@@ -119,7 +105,7 @@ from datasets import load_dataset
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  sample = load_dataset("DatasetSubmission/HackerSignal", "sample")
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  # Load a benchmark task
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- task1 = load_dataset("DatasetSubmission/HackerSignal", "task1_exploit_clf")
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  # Load the full corpus (12 GB)
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  full = load_dataset("DatasetSubmission/HackerSignal", "default")
@@ -140,17 +126,8 @@ full = load_dataset("DatasetSubmission/HackerSignal", "default")
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  ## Benchmark Tasks
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- ### Task 1: Exploit Relevance Classification
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- Binary classification (exploit-relevant vs. not). Cross-source labeling: positives are CVE-mentioning posts from exploit/advisory sources; negatives are non-CVE hacker community posts. Temporal split: train (<2022), val (2022--2023), test (2024+).
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-
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- | Split | Rows |
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- |-------|------|
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- | Train | 89,906 |
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- | Val | 1,400 |
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- | Test | 1,236 |
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-
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- ### Task 2: CVE Linkage Retrieval
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- Given source evidence text, retrieve the correct NVD CVE entry from a corpus of 340K descriptions. Quality-controlled to remove unretrievable rows.
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  | Split | Rows |
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  |-------|------|
@@ -159,32 +136,24 @@ Given source evidence text, retrieve the correct NVD CVE entry from a corpus of
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  | Test | 550 |
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  | Corpus | 340,536 |
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- ### Task 3: Severity Prediction
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- 4-class CVSS severity prediction (low/medium/high/critical) from advisory text with explicit severity strings stripped.
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-
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- | Split | Rows |
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- |-------|------|
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- | Train | 6,797 |
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- | Val | 12,836 |
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- | Test | 11,711 |
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-
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- ### Task 4: Hacker Exploit Labeling
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- Ternary weak-supervision task: 0=non-exploit/noise, 1=vulnerability discussion, 2=actionable exploit.
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  | Split | Rows |
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  |-------|------|
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- | Train | 200,382 |
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- | Val | 1,933 |
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- | Test | 100,963 |
 
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- ### Task 5: Hacker Exploit Signal Detection
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- Joint detection + retrieval: identify actionable exploit signals and link to NVD CVE context. 10:1 negative-to-positive ratio reflects real-world signal rarity.
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  | Split | Rows |
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  |-------|------|
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- | Train | 4,202 |
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- | Val | 1,606 |
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- | Test | 407 |
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  | Corpus | 340,536 |
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  ## Schema
 
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  data_files:
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  - split: full
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  path: hackersignal_sample_10k.jsonl
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+ - config_name: task1_cve_linkage
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  data_files:
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  - split: train
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+ path: benchmark_v2/task1_cve_linkage/train.jsonl
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  - split: validation
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+ path: benchmark_v2/task1_cve_linkage/val.jsonl
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  - split: test
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+ path: benchmark_v2/task1_cve_linkage/test.jsonl
 
 
 
 
 
 
 
 
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  - split: corpus
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+ path: benchmark_v2/task1_cve_linkage/corpus.jsonl
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+ - config_name: task2_signal_detection
 
 
 
 
 
 
 
 
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  data_files:
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  - split: train
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+ path: benchmark_v2/task2_signal_detection/train.jsonl
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  - split: validation
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+ path: benchmark_v2/task2_signal_detection/val.jsonl
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  - split: test
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+ path: benchmark_v2/task2_signal_detection/test.jsonl
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+ - split: corpus
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+ path: benchmark_v2/task2_signal_detection/corpus.jsonl
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+ - config_name: task3_temporal_generalization
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  data_files:
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  - split: train
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+ path: benchmark_v2/task3_temporal_generalization/train.jsonl
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  - split: validation
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+ path: benchmark_v2/task3_temporal_generalization/val.jsonl
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  - split: test
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+ path: benchmark_v2/task3_temporal_generalization/test.jsonl
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  - split: corpus
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+ path: benchmark_v2/task3_temporal_generalization/corpus.jsonl
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  ---
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84
  # HackerSignal
 
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  | Source layers | 8 |
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  | Temporal span | 1988--2026 |
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  | CVE-linked rows | 360,004 |
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+ | Benchmark tasks | 3 |
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  ## Quick Start
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  sample = load_dataset("DatasetSubmission/HackerSignal", "sample")
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  # Load a benchmark task
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+ task1 = load_dataset("DatasetSubmission/HackerSignal", "task1_cve_linkage")
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  # Load the full corpus (12 GB)
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  full = load_dataset("DatasetSubmission/HackerSignal", "default")
 
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  ## Benchmark Tasks
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+ ### Task 1: CVE Linkage Retrieval (CVE-R)
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+ Cross-source temporally OOD entity grounding: given exploit/advisory evidence text, retrieve the correct NVD CVE entry from a corpus of 340K descriptions. Quality-controlled to remove unretrievable rows.
 
 
 
 
 
 
 
 
 
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  | Split | Rows |
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  |-------|------|
 
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  | Test | 550 |
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  | Corpus | 340,536 |
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+ ### Task 2: Hacker Signal Detection (HSD)
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+ Two-stage task: (1) detect actionable exploit signals from hacker community noise, (2) ground positives to NVD CVE. 10:1 negative-to-positive ratio reflects real-world signal rarity.
 
 
 
 
 
 
 
 
 
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  | Split | Rows |
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  |-------|------|
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+ | Train | 4,202 |
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+ | Val | 1,606 |
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+ | Test | 407 |
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+ | Corpus | 340,536 |
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+ ### Task 3: Temporal Generalization (TG)
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+ Identical retrieval formulation to Task 1 but with strict CVE-disjoint constraint: C_train C_test = ∅. Split by CVE publication year (train: <2022, test: 2024+) to test generalization to wholly unseen vulnerabilities.
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  | Split | Rows |
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  |-------|------|
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+ | Train | 41,630 |
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+ | Val | 1,776 |
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+ | Test | 393 |
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  | Corpus | 340,536 |
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  ## Schema