Latest Natural Language Processing Research Papers

Research on text understanding, sentiment analysis, named entity recognition, and linguistic AI applications.

7 Papers

Showing 7 of 7 papers

Beyond Cosine Similarity: Taming Semantic Drift and Antonym Intrusion in a 15-Million Node Turkish Synonym Graph

Ebubekir Tosun, Mehmet Emin Buldur, Özay Ezerceli +1 more

Neural embeddings have a notorious blind spot: they can't reliably tell synonyms apart from antonyms. Consequently, increasing similarity thresholds often fails to prevent opposites from being grouped together. We've built a large-scale semantic clustering system specifically designed to tackle this...

semantic clusteringneural embeddingssynonymyantonymyco-hyponymy+7 more

Jan 19, 20263

A Hybrid Protocol for Large-Scale Semantic Dataset Generation in Low-Resource Languages: The Turkish Semantic Relations Corpus

Ebubekir Tosun, Mehmet Emin Buldur, Özay Ezerceli +1 more

We present a hybrid methodology for generating large-scale semantic relationship datasets in low-resource languages, demonstrated through a comprehensive Turkish semantic relations corpus. Our approach integrates three phases: (1) FastText embeddings with Agglomerative Clustering to identify semanti...

FastText embeddingsAgglomerative Clusteringsemantic relationship classificationsemantic clustersdownstream tasks+2 more

Jan 19, 20263

Patient-Similarity Cohort Reasoning in Clinical Text-to-SQL

Yifei Shen, Yilun Zhao, Justice Ou +2 more

Real-world clinical text-to-SQL requires reasoning over heterogeneous EHR tables, temporal windows, and patient-similarity cohorts to produce executable queries. We introduce CLINSQL, a benchmark of 633 expert-annotated tasks on MIMIC-IV v3.1 that demands multi-table joins, clinically meaningful fil...

text-to-SQLEHR tablesclinical reasoningmulti-table joinstemporal windows+9 more

Jan 14, 20264

Cluster Workload Allocation: Semantic Soft Affinity Using Natural Language Processing

Leszek Sliwko, Jolanta Mizeria-Pietraszko

Cluster workload allocation often requires complex configurations, creating a usability gap. This paper introduces a semantic, intent-driven scheduling paradigm for cluster systems using Natural Language Processing. The system employs a Large Language Model (LLM) integrated via a Kubernetes schedule...

Jan 14, 2026

TranslateGemma Technical Report

Mara Finkelstein, Isaac Caswell, Tobias Domhan +17 more

We present TranslateGemma, a suite of open machine translation models based on the Gemma 3 foundation models. To enhance the inherent multilingual capabilities of Gemma 3 for the translation task, we employ a two-stage fine-tuning process. First, supervised fine-tuning is performed using a rich mixt...

Jan 13, 20261

Benchmarking Small Language Models and Small Reasoning Language Models on System Log Severity Classification

Yahya Masri, Emily Ma, Zifu Wang +2 more

System logs are crucial for monitoring and diagnosing modern computing infrastructure, but their scale and complexity require reliable and efficient automated interpretation. Since severity levels are predefined metadata in system log messages, having a model merely classify them offers limited stan...

Jan 12, 2026

A Rising Tide Lifts All Boats: MTQE Rewards for Idioms Improve General Translation Quality

Ishika Agarwal, Zhenlin He, Dhruva Patil +1 more

Non-compositional expressions (e.g., idioms, proverbs, and metaphors) pose significant challenges for neural machine translation systems because their meanings cannot be derived from individual words alone. These expressions encode rich, cultural meaning, and have both figurative and literal meaning...

Jan 9, 2026

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