Qwen2.5-1.5B
qwen2-5-1-5b-f74d5c16·2 events·first seen 21d agoAliases: Qwen2.5-1.5B
Co-occurring entities
More like this (12)
Recent events (2)
Separating Semantic Competition from Context Length in RAG Reading
This paper introduces a matched-control protocol to isolate whether RAG reader failures stem from context length or semantic competition among retrieved passages. By replacing hard-competitor passages with less competitive ones while holding passage count and length fixed, the authors demonstrate a measurable competition effect on SQuAD using Phi-2 and Qwen2.5-1.5B. Phi-2 recovers +6.0 EM and +7.0 answer-inclusion points; Qwen2.5-1.5B recovers +4.5 EM and +9.0 answer-inclusion points. The study also introduces retention curves and a right-censored half-life metric to track performance degradation as competitors accumulate.
Multi-source cybersecurity log dataset with ATT&CK labels and SLM fine-tuning evaluation
Researchers introduce a new multi-source cybersecurity log dataset of 870 sessions (~2.3M events) capturing system, network, and browser activity on Windows endpoints, with per-entry MITRE ATT&CK technique labels across 12 tactics and 53 techniques. The dataset addresses gaps in existing public datasets (CICIDS, UNSW-NB15, ATLAS) that lack combined multi-source coverage with fine-grained ATT&CK labeling. Three small language models (Qwen2.5-1.5B, Llama-3.2-3B, Phi-4-Mini) were fine-tuned with LoRA on the dataset, achieving chunk classification accuracy of 90–97% versus ~8% for base variants, though ATT&CK technique identification remained harder at 42% exact-match accuracy.