51 citations · 53 across the 11 of their papers we have counts for
13 papers
Adaptive Test-Time Inference for Text2Cypher with Trace Budgeting and Selective Refinement
Makbule Gulcin Ozsoy
Large language models have enabled natural language interfaces for structured databases, but generated queries may still contain syntactic errors, violate database schemas, or fail…
Toward Multi-Database Query Reasoning for Text2Cypher
Makbule Gulcin Ozsoy
Large language models have significantly improved natural language interfaces to databases by translating user questions into executable queries. In particular, Text2Cypher focuses…
Extending Confidence-Based Text2Cypher with Grammar and Schema Aware Filtering
Makbule Gulcin Ozsoy
Large language models (LLMs) allow users to query databases using natural language by translating questions into executable queries. Despite strong progress on tasks such as Text2S…
Incremental Multilingual Text2Cypher with Adapter Combination
Makbule Gulcin Ozsoy
Large Language Models enable users to access database using natural language interfaces using tools like Text2SQL, Text2SPARQL, and Text2Cypher, which translate user questions into…
Text2Cypher Across Languages: Evaluating and Finetuning LLMs
Makbule Gulcin Ozsoy, William Tai
Recent advances in large language models (LLMs) have enabled natural language interfaces that translate user questions into database queries, such as Text2SQL, Text2SPARQL, and Tex…
Text2Cypher: Data Pruning using Hard Example Selection
Makbule Gulcin Ozsoy
Database query languages such as SQL for relational databases and Cypher for graph databases have been widely adopted. Recent advancements in large language models (LLMs) enable na…
Enhancing Text2Cypher with Schema Filtering
Makbule Gulcin Ozsoy
Knowledge graphs represent complex data using nodes, relationships, and properties. Cypher, a powerful query language for graph databases, enables efficient modeling and querying.…
Text2Cypher: Bridging Natural Language and Graph Databases
Makbule Gulcin Ozsoy, Leila Messallem, Jon Besga +1
Knowledge graphs use nodes, relationships, and properties to represent arbitrarily complex data. When stored in a graph database, the Cypher query language enables efficient modeli…
Multilingual Prompts in LLM-Based Recommenders: Performance Across Languages
Makbule Gulcin Ozsoy
Large language models (LLMs) are increasingly used in natural language processing tasks. Recommender systems traditionally use methods such as collaborative filtering and matrix fa…
Multi-Margin Cosine Loss: Proposal and Application in Recommender Systems
Makbule Gulcin Ozsoy
Recommender systems guide users through vast amounts of information by suggesting items based on their predicted preferences. Collaborative filtering-based deep learning techniques…
Beyond Next Item Recommendation: Recommending and Evaluating List of Sequences
Makbule Gulcin Ozsoy
Recommender systems (RS) suggest items-based on the estimated preferences of users. Recent RS methods utilise vector space embeddings and deep learning methods to make efficient re…
Utilizing FastText for Venue Recommendation
Makbule Gulcin Ozsoy
Venue recommendation systems model the past interactions (i.e., check-ins) of the users and recommend venues. Traditional recommendation systems employ collaborative filtering, con…
From Word Embeddings to Item Recommendation
Makbule Gulcin Ozsoy
Social network platforms can use the data produced by their users to serve them better. One of the services these platforms provide is recommendation service. Recommendation system…