Papers with random walk
GNEG: Graph-Based Negative Sampling for word2vec (P18-2)
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| Challenge: | Generally speaking, negative sampling is the best choice for distributed word representation learning. |
| Approach: | They hypothesize that taking into account global, corpus-level information and generating a different noise distribution for each target word better satisfies the requirements of negative examples for each training word. |
| Outcome: | The proposed approach boosts the word analogy task by about 5% and improves the performance on word similarity tasks by about 11% compared to the baseline. |
Hidden Schema Networks (2023.acl-long)
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| Challenge: | Existing models that encode rich semantic and syntactic content are biased, but they are effective at encoding symbolic representations. |
| Approach: | They propose a neural language model that enforces explicit relational structures which allow for compositionality onto the output representations of pretrained language models. |
| Outcome: | The proposed model can encode sentences into sequences of symbols and infer the posterior distribution of the model from natural language datasets. |
Breaking the Static Graph: Context-Aware Traversal for Graph-Based RAG (2026.findings-acl)
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| Challenge: | Recent advances in RAG focus on capturing multi-hop dependencies, but static Graphs fail to retrieve complete evidence chain. |
| Approach: | They propose a structure-aware approach to capture multi-hop dependencies using Knowledge Graphs and Personalized PageRank to capture semantic drift. |
| Outcome: | Experiments show that CatRAG outperforms state-of-the-art approaches . the proposed approach achieves substantial improvements in reasoning completeness . |
English WordNet Random Walk Pseudo-Corpora (2020.lrec-1)
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| Challenge: | a random walk over the WordNet taxonomy generates a set of pseudo-corpora . a resource description paper describes the creation and properties of such pseudo-corporates . |
| Approach: | They propose to use random walk to generate a set of pseudo-corpora over the English WordNet taxonomy. |
| Outcome: | The proposed pseudo-corpora can be used to train taxonomic word embeddings . the proposed pseudo corpora are generated from a random walk over the English wordnet taxonomy . |
Exploring Human Gender Stereotypes with Word Association Test (D19-1)
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| Challenge: | Existing word embeddings have been used to study gender stereotypes in texts . however, evaluating their validities is still an open problem . et al.: this study investigates gender bias using the lens of language, especially, the words . |
| Approach: | They use word association test to derive bias scores for large amount of words . they find that these bias scores correlate well with bias in the real world . |
| Outcome: | The proposed method correlates well with bias in the real world, and with census data, it provides a different perspective on gender stereotypes in words. |