Knowledge distillation

Evidence in the last complete seven days

Source mentions

1

Previous seven days 1

Distinct sources

1

Previous 1

Comparable growth

Not comparable

Ranking appearances

0

Collection observations and undated records are separate from dated publication counts. Observed in 7d：0 · Undated records：0

Daily history · up to 90 days

Bars show dated source mentions. The latest UTC day may be incomplete. Zero mentions and missing collection coverage are different conditions.

Dotted markers indicate days with no record. They are not counted as zero mentions.

Source evidence

Sources in the evidence shown：arXiv 3

1. arXiv · Published Nov 10, 2026

   MambaLoc: Lightweight Indoor Localization Using Cross-Modal Knowledge Distillation

   arXiv:2611.10360v1 Announce Type: new Abstract: Accurate indoor localization on resource-constrained edge devices remains challenging due to the tension between modeling fidelity and computational efficiency. Wi-Fi Channel State Information (CSI) enables low-cost deployment using existing Wi-Fi infrastructure but is heavily distorted by multipath propagation

   View source record →

2. arXiv · Published Oct 29, 2026

   From Solver Trajectories to Teaching Trajectories: Cognition-Aligned Reasoning Distillation

   arXiv:2610.36445v1 Announce Type: new Abstract: Knowledge distillation from large reasoning models (LRMs) often uses raw teacher trajectories as supervision. However, this practice creates a mismatch between the goal of distillation and the nature of teacher trajectories. Advanced LRMs typically improve their reasoning capabilities through reward-driven post

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3. arXiv · Published Oct 22, 2026

   D-Skill: Distilling Teacher Knowledge through Agent Skills

   arXiv:2610.28914v1 Announce Type: new Abstract: Frontier language-model agents excel at complex tasks, but high inference costs make transferring their capabilities to smaller models essential. Traditional knowledge distillation achieves this through parameter updates, requiring access to the student's weights and additional training compute while encoding t

   View source record →

Review priority 41 / 100

This score orders research candidates. It is not search volume, a forecast or verified commercial demand.

• Evidence

  8 / 30

  Distinct dated articles or first observations; repeat crawling adds nothing.

• Publisher diversity

  8 / 25

  Conservative owner grouping; syndicated copies count once.

• Comparable change

  0 / 20

  Comparable complete weeks only; no percentage from a zero baseline.

• Recent evidence

  15 / 15

  Latest publication or first observation, not repeated fetch time.

• Name specificity

  9.7 / 10

  Explicit entities and technical concepts outrank ambiguous acronyms.

Limitations and interpretation

• First observation is a collection milestone, not proof that a word or product is new to the world.
• Counts describe monitored public sources, not the whole web or search demand.
• First observed here is not the invention date of a name or idea.
• Candidates come from public titles, summaries and entity URLs, not verified full-text analysis.
• Owner grouping is conservative; undisclosed syndication may remain.
• An established concept or common product name retained as a baseline, not a newly invented term.
• The previous week is too small for a reliable percentage change.
• Current evidence comes from one publisher or owner.