4 citations · 5 across the 14 of their papers we have counts for
4 papers · 2 filters
Do LLMs Align with My Task? Evaluating Text-to-SQL via Dataset Alignment
Davood Rafiei, Morgan Lindsay Heisler, Weiwei Zhang +2
Supervised Fine-Tuning (SFT) is an effective method for adapting Large Language Models (LLMs) on downstream tasks. However, variability in training data can hinder a model's abilit…
Rethinking Schema Linking: A Context-Aware Bidirectional Retrieval Approach for Text-to-SQL
Md Mahadi Hasan Nahid, Davood Rafiei, Weiwei Zhang +1
Schema linking -- the process of aligning natural language questions with database schema elements -- is a critical yet underexplored component of Text-to-SQL systems. While recent…
Continuous Self-Improvement of Large Language Models by Test-time Training with Verifier-Driven Sample Selection
Mohammad Mahdi Moradi, Hossam Amer, Sudhir Mudur +3
Learning to adapt pretrained language models to unlabeled, out-of-distribution data is a critical challenge, as models often falter on structurally novel reasoning tasks even while…
Balancing Computation Load and Representation Expressivity in Parallel Hybrid Neural Networks
Mohammad Mahdi Moradi, Walid Ahmed, Shuangyue Wen +3
Attention and State-Space Models (SSMs) when combined in a hybrid network in sequence or in parallel provide complementary strengths. In a hybrid sequential pipeline they alternate…