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Progress-Aware Distillation for Mitigating Stagnation in Small Language Model Agents

While LLM-based agent systems have demonstrated remarkable proficiency in reasoning and solving complex real-world tasks, they also come with substantial token consumption and inference latency, limit

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#16Best rank
–Score · 24h
73Score · 7d
2Days on list
8Snapshots
Oct 20, 2026First seen

Summary

Progress-Aware Distillation for Mitigating Stagnation in Small Language Model Agents was first seen on Hugging Face · Daily papers on Oct 20, 2026. Since then it appeared in 8 hourly checks across 2 days, peaking at #16 on Oct 21, 05:18 UTC. It was last on the list on Oct 21, 07:18 UTC.

Rank history

Position on Hugging Face · Daily papers at every check (lower is better).

#1#11#20#30 17:1720:4700:1703:4807:18 Oct 20, 17:17 UTC · #30Oct 20, 19:18 UTC · #30Oct 20, 21:18 UTC · #28Oct 20, 23:18 UTC · #27Oct 21, 01:18 UTC · #23Oct 21, 03:18 UTC · #20Oct 21, 05:18 UTC · #16Oct 21, 07:18 UTC · #20

Last 14 days

Best rank per day (UTC).

Oct 14today

Metric history

Platform metric as reported by Hugging Face.

0358 17:1720:4700:1703:4807:18 Oct 20, 17:17 UTC · 6Oct 20, 19:18 UTC · 6Oct 20, 21:18 UTC · 6Oct 20, 23:18 UTC · 6Oct 21, 01:18 UTC · 7Oct 21, 03:18 UTC · 8Oct 21, 05:18 UTC · 8Oct 21, 07:18 UTC · 8

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Progress-Aware Distillation for Mitigating Stagnation in Small Language Model Agents on TrendBoard
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