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New Term Radar
Discover names and concepts appearing in public sources, with dated evidence, source coverage and comparable growth.
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Collection coverage · Comparable windowsCurrent / previous observed days 7 / 7
Counts use complete UTC days. First observed means first seen by this collection, not when a term was coined.
Current window:2026-10-31 → 2026-11-07 (end excluded) · History 19 days
| Source | Current days | Previous days | Last success |
|---|---|---|---|
| arXiv | 6 | 5 | Nov 7, 2026, 12:45 AM UTC |
| arXiv | 7 | 4 | Nov 7, 2026, 5:30 AM UTC |
| Ask HN | 7 | 5 | Nov 7, 2026, 4:30 PM UTC |
| Ask HN | 7 | 5 | Nov 7, 2026, 4:30 PM UTC |
| Ask HN | 7 | 5 | Nov 7, 2026, 4:45 PM UTC |
| Ask HN | 7 | 5 | Nov 7, 2026, 4:45 PM UTC |
| GitHub | 7 | 5 | Nov 7, 2026, 1:15 PM UTC |
| GitHub Issues | 7 | 5 | Nov 7, 2026, 4:15 PM UTC |
| GitHub Releases | 7 | 3 | Nov 7, 2026, 12:45 PM UTC |
| GitHub | 7 | 5 | Nov 7, 2026, 2:45 PM UTC |
| GitHub Issues | 7 | 5 | Nov 7, 2026, 5:15 PM UTC |
| GitHub Releases | 7 | 5 | Nov 7, 2026, 5:15 PM UTC |
| GitHub | 7 | 5 | Nov 7, 2026, 2:45 PM UTC |
| GitHub Issues | 7 | 5 | Nov 7, 2026, 5:30 PM UTC |
| GitHub Releases | 7 | 5 | Nov 7, 2026, 5:15 PM UTC |
| GitHub Discovery | 2 | 0 | Nov 7, 2026, 4:45 PM UTC |
| GitHub Trending | 7 | 5 | Nov 7, 2026, 8:00 PM UTC |
| 7 | 4 | Nov 7, 2026, 8:45 AM UTC | |
| Hugging Face | 7 | 4 | Nov 7, 2026, 8:45 AM UTC |
| Hugging Face Spaces | 2 | 0 | Nov 7, 2026, 4:30 PM UTC |
| Hacker News | 7 | 5 | Nov 7, 2026, 8:00 PM UTC |
| Hacker News | 7 | 5 | Nov 7, 2026, 4:45 PM UTC |
| Hacker News | 7 | 5 | Nov 7, 2026, 4:45 PM UTC |
| Hacker News | 2 | 0 | Nov 7, 2026, 4:45 PM UTC |
| Show HN | 2 | 0 | Nov 7, 2026, 4:45 PM UTC |
| MIT News | 7 | 4 | Nov 7, 2026, 5:45 PM UTC |
| OpenAI | 7 | 5 | Nov 7, 2026, 11:45 AM UTC |
| Product Hunt | 7 | 5 | Nov 7, 2026, 8:00 PM UTC |
| 量子位 | 6 | 5 | Nov 6, 2026, 7:00 PM UTC |
| OpenRouter | 2 | 0 | Nov 7, 2026, 10:05 PM UTC |
| GitHub Trending | 7 | 7 | Nov 6, 2026, 1:15 PM UTC |
| Hugging Face Models | 2 | 0 | Nov 7, 2026, 10:05 PM UTC |
| HF Daily Papers | 2 | 0 | Nov 7, 2026, 10:05 PM UTC |
| OpenRouter | 2 | 0 | Nov 7, 2026, 10:05 PM UTC |
| Product Hunt | 7 | 7 | Nov 6, 2026, 1:15 PM UTC |
| SEC EDGAR | 7 | 5 | Nov 7, 2026, 10:45 AM UTC |
| Sequoia Capital | 7 | 4 | Nov 7, 2026, 6:45 AM UTC |
| Simon Willison | 2 | 0 | Nov 7, 2026, 3:30 PM UTC |
| TechCrunch | 7 | 5 | Nov 7, 2026, 9:45 PM UTC |
| Contracts Finder | 7 | 5 | Nov 7, 2026, 8:15 PM UTC |
| V2EX | 7 | 5 | Nov 7, 2026, 9:45 PM UTC |
- Counts describe monitored public sources, not the whole web or search demand.
Seven-day figures use the complete UTC window above. Priority is a research triage score, not search volume, market size or a probability of success.
PerMIT
arXiv:2610.28987v1 Announce Type: new Abstract: Persistent memory is a largely undefended surface for injection and poisoning, and the same risk limits memory sharing among agents. We present PerMIT, a memory architecture with provable integrity guarantees under an explicit trust assumption: only user-typed inputs and values confirmed at a gate are trusted.
First observed Oct 22, 2026 · arXiv
- 7d mentions
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- 9 / 100
MSA
arXiv:2610.30344v1 Announce Type: new Abstract: Training Arabic large language models faces challenges from noisy web data, dialectal variation, and the high cost of continual pretraining (CPT). We introduce AQL-Lite (AQL: Arabic Quality Language), a time- and resource-efficient framework for adapting a multilingual LLM to Modern Standard Arabic (MSA). AQL-L
First observed Oct 24, 2026 · arXiv
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- 9 / 100
Secondhand Stress
First observed Oct 19, 2026 · arXiv
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- 9 / 100
Aw-1
First observed Oct 21, 2026 · Hacker News
- 7d mentions
- 0 previous 0
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- 9 / 100
TauIndianBankBench
arXiv:2610.30161v1 Announce Type: new Abstract: Many Indian banks serve customers through FAQ pages and scripted chatbots. Assistants based on language models could respond faster and carry out requests such as blocking a card, but only if they give correct information and follow the bank's rules. These rules prescribe a procedure, a set of required steps, s
First observed Oct 24, 2026 · arXiv
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- 9 / 100
FlashMap
First observed Oct 20, 2026 · arXiv
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- 9 / 100
StoreBench
First observed Oct 9, 2026 · arXiv
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- 0 previous 0
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- 9 / 100
HeRE
First observed Oct 19, 2026 · arXiv
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- 9 / 100
Higherlevel
First observed Oct 10, 2026 · Hacker News
- 7d mentions
- 0 previous 0
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- 9 / 100
Vibetown
First observed Oct 19, 2026 · Hacker News
- 7d mentions
- 0 previous 0
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- 9 / 100
HERO
First observed Oct 16, 2026 · arXiv
- 7d mentions
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- 9 / 100
Behind Aggregate Scores
arXiv:2610.30512v1 Announce Type: new Abstract: LLM judges are used to determine which of two answers is better. Trusting these verdicts requires knowing how repeatable they are and how much they depend on the judge's instructions. We show that similar aggregate scores can conceal substantial changes in individual verdicts, both when the same setup is repeat
First observed Oct 24, 2026 · arXiv
- 7d mentions
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- 9 / 100
H2DF
arXiv:2610.26864v1 Announce Type: new Abstract: Gradient ascent (GA) is a simple language-model unlearning baseline, but it continues increasing forget loss after useful forgetting has occurred. This unbounded pressure can damage retained utility and make forgotten examples abnormally high-loss. We introduce H2DF, a calibrated target-band objective that appl
First observed Oct 22, 2026 · arXiv
- 7d mentions
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- 9 / 100
AuditKIT
First observed Oct 19, 2026 · arXiv
- 7d mentions
- 0 previous 0
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- 9 / 100
SteerSearch
First observed Oct 20, 2026 · arXiv
- 7d mentions
- 0 previous 0
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- 0
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- 9 / 100
Algebras Harness
First observed Oct 20, 2026 · Hacker News
- 7d mentions
- 0 previous 0
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- 9 / 100
AutoIndexer
First observed Oct 12, 2026 · arXiv
- 7d mentions
- 0 previous 0
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- 9 / 100
HedgePick
First observed Oct 18, 2026 · Hacker News
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- 0 previous 0
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- 0
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- 9 / 100
Tune-Up
First observed Oct 11, 2026 · Hacker News
- 7d mentions
- 0 previous 0
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- 0
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- 9 / 100
FusionEval
arXiv:2610.30162v1 Announce Type: new Abstract: Model fusion aims to integrate the capabilities of multi-expert models into a single model. Existing evaluations offer limited coverage of reasoning with long chains of thought and tool use, while strong average performance can mask substantial losses in individual expert capabilities. We introduce FusionEval,
First observed Oct 24, 2026 · arXiv
- 7d mentions
- 0 previous 1
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- 9 / 100
GardenBench
First observed Oct 20, 2026 · arXiv
- 7d mentions
- 0 previous 0
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- 9 / 100
Ex-Nvidia-turned-VC Amulya Vishwanath
It’s the moment everyone is waiting for — the ChatGPT moment for robotics, Amulya Vishwanath explained to TechCrunch’s Equity.
First observed Oct 20, 2026 · TechCrunch
- 7d mentions
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- 9 / 100
Virgil
First observed Oct 10, 2026 · Hacker News
- 7d mentions
- 0 previous 0
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- 0
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- 9 / 100
HiRO-ACEv2
First observed Oct 15, 2026 · Hugging Face
- 7d mentions
- 0 previous 0
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- 9 / 100
AQL-Lite
arXiv:2610.30344v1 Announce Type: new Abstract: Training Arabic large language models faces challenges from noisy web data, dialectal variation, and the high cost of continual pretraining (CPT). We introduce AQL-Lite (AQL: Arabic Quality Language), a time- and resource-efficient framework for adapting a multilingual LLM to Modern Standard Arabic (MSA). AQL-L
First observed Oct 24, 2026 · arXiv
- 7d mentions
- 0 previous 1
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- 0
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- 9 / 100
Evaluating Compressed Memory
First observed Oct 16, 2026 · arXiv
- 7d mentions
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- 9 / 100
AtomSD
arXiv:2610.26926v1 Announce Type: new Abstract: Large language models (LLMs) possess broad factual knowledge and strong reasoning capabilities, but solving complex tasks also requires procedural knowledge about how to act. Existing approaches often represent procedural knowledge through trajectories or bundled skills, limiting flexible reuse across interacti
First observed Oct 22, 2026 · arXiv
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- 9 / 100
Cognitive Thermometers
First observed Oct 9, 2026 · arXiv
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Route-and-Generate
arXiv:2610.30351v1 Announce Type: new Abstract: Large language models often apply complex reasoning indiscriminately, leading to overthinking on simple tasks and underthinking on harder ones. We present Route-and-Generate (Rouge), a hierarchical training framework that enables LLMs to adaptively decide when and how much reasoning is required for each input.
First observed Oct 23, 2026 · arXiv
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KIRA
arXiv:2610.28840v1 Announce Type: new Abstract: Early-grade reading screening is critical for identifying children at risk of reading difficulty. Existing AI-based screeners are often limited in the scope of their analyses and evaluation metrics, or are proprietary systems that lack transparent model specifications and evaluation. We present KIRA, a dual-pat
First observed Oct 23, 2026 · arXiv
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