Large language model
AI Tools · first detected 8 Aug 2026 · scored 6 Oct 2026
Trend score
0/100
Opportunity
0/100
Confidence
66%
Trend, 30 days
Why this score
- −No source shows a clear spike yet
- −Flat week over week
- −Already covered heavily (saturation 48%)
- ·Not scored on arXiv (source unavailable); weights rebalanced
How this score was calculated
| Component | Value | Weight | Points |
|---|---|---|---|
| Attention growth | 0% | 0.40 | +0.0 |
| Coverage growth | 0% | 0.00 | +0.0 |
| Cross-source breadth | 0% | 0.27 | +0.0 |
| Acceleration | 0% | 0.20 | +0.0 |
| Freshness | 0% | 0.13 | +0.0 |
| Saturation (subtracted) | 48% | 0.25 | −11.9 |
| Trend score (0–100) | 0.0 |
Opportunity = trend 0.0 × (1 − saturation 48%) × stage weight 0.4 × niche relevance 1 = 0.0
Saturation parts: volume 95%, time elevated 0%, mainstream 0%. Spike ratio = mean of the last 3 days ÷ median of days 4–31. A source counts as spiking at ≥ 1.5× and robust z ≥ 2.
| Source | Spike | Robust z | Week over week | Spiking |
|---|---|---|---|---|
| wikipedia | 0.92× | -0.6 | -3% | no |
Full method: methodology. Rising means rising now; it is not a prediction that a topic will go viral.
Signals by source
Wikipedia views
4K/day
2026-09-07 → 2026-10-06 · fetched 7 Oct, 12:50 UTC
New arXiv papers
74/day
2026-09-07 → 2026-10-06 · fetched 7 Oct, 11:45 UTC · not used in today's score
Attention data: Wikipedia pageviews via the Wikimedia Analytics API · Research data: arXiv (thank you to arXiv for use of its open access interoperability) · Data as of 7 Oct, 12:50 UTC
Licences and terms
- Attention data: Wikipedia pageviews via the Wikimedia Analytics API: CC0 (pageview data)
- Research data: arXiv (thank you to arXiv for use of its open access interoperability): Metadata CC0
Key headlines
- Secure Speculative Decoding for Large Language ModelsarXiv · arxiv.org · 6 Oct 2026
- Towards In-Parameter Memory Augmentation for Large Language ModelsarXiv · arxiv.org · 6 Oct 2026
- Incidental information contaminates patient notes and disrupts clinical reasoning in large language modelsarXiv · arxiv.org · 6 Oct 2026
- RSJEV: Discriminative Remote Sensing Scene Classification with Multimodal Large Language ModelsarXiv · arxiv.org · 6 Oct 2026
- zkLLMPoT: Efficient Zero Knowledge Proof of Training for Large Language ModelsarXiv · arxiv.org · 6 Oct 2026
- Align, Then Correct: Training-Free Two-Stage Low-Rank Compensation for Extremely Quantized Large Language ModelsarXiv · arxiv.org · 6 Oct 2026
- Pseudowords as probes: Large Language Models show little of the sublexical sensitivity that governs human pseudoword processingarXiv · arxiv.org · 6 Oct 2026
- Dynamic Positional Attention Modulation for Parameter-Efficient Fine-Tuning of Large Language ModelsarXiv · arxiv.org · 6 Oct 2026
- Large Language Model Orchestration under Heterogeneous Preferences via Explicit Persona InferencearXiv · arxiv.org · 6 Oct 2026
- HouseholdBench: Evaluating Large Language Models as Predictors of Household Economic BehaviorarXiv · arxiv.org · 6 Oct 2026
Each headline opens the original article on the publisher's site. We show headlines and links only and never republish article text.
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What to make about it
Content angles are written once a topic passes the publish threshold.
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