Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Modeling Quantum Entanglements in Quantum Language Models
Authors: Mengjiao Xie, Yuexian Hou, Peng Zhang, Jingfei Li, Wenjie Li, Dawei Song
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We empirically compare our model with related models, and the results demonstrate the effectiveness of our model. |
| Researcher Affiliation | Academia | 1School of Computer Science and Technology, Tianjin University, China 2Department of Computing, The Hong Kong Polytechnic University, Hong Kong 3Department of Computing and Communications, The Open University, UK |
| Pseudocode | Yes | Algorithm 1 Build the sequence of projectors SD for D. |
| Open Source Code | No | The paper does not provide any explicit statements or links indicating that the source code for the methodology is openly available. |
| Open Datasets | Yes | We conduct experiments on ๏ฌve collections in the documents re-ranking task. Table 2 describes the collections in detail. |
| Dataset Splits | No | The paper mentions using |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., GPU models, CPU models, memory) used for running the experiments. |
| Software Dependencies | Yes | The collections have been stemmed with the Porter stemmer and processed with the standard stop word list when using the Lemur 4.12 for building index. |
| Experiment Setup | Yes | For all the models, we apply the Dirichlet smoothing method [Zhai, 2008] in which the parameter ยต is set to be a typical value 2500. The unconditional pure dependence patterns with at most three orders are taken into account, in order to reduce the computational cost. The length of the unordered ๏ฌxed window in Algorithm 1 is set to be: L = 4 |K|, where |K| is the numbers of terms appearing in the UPD pattern K [Metzler and Croft, 2005]. |