From the 1 of 16 linked papers with an AI index.
2 citations · 2 across the 11 of their papers we have counts for
10 papers · 1 filter
Rose-SQL: Role-State Evolution Guided Structured Reasoning for Multi-Turn Text-to-SQL
Le Zhou, Feng Yao, Fengcai Qiao +3
Recent advances in Large Reasoning Models (LRMs) trained with Long Chain-of-Thought have demonstrated remarkable capabilities in code generation and mathematical reasoning. However…
SAM-NER: Semantic Archetype Mediation for Zero-Shot Named Entity Recognition
Ruichu Cai, Juntao Gan, Miao Mai +2
Zero-shot Named Entity Recognition (ZS-NER) remains brittle under domain and schema shifts, where unseen label definitions often misalign with a large language model's (LLM's) intr…
SERE: Structural Example Retrieval for Enhancing LLMs in Event Causality Identification
Zhifeng Hao, Zhongjie Chen, Junhao Lu +5
Event Causality Identification (ECI) requires models to determine whether a given pair of events in a context exhibits a causal relationship. While Large Language Models (LLMs) hav…
IT: Stepwise Syntax Integration Tuning for Large Language Models in Aspect Sentiment Quad Prediction
Bingfeng Chen, Chenjie Qiu, Yifeng Xie +3
Aspect Sentiment Quad Prediction (ASQP) has seen significant advancements, largely driven by the powerful semantic understanding and generative capabilities of large language model…
Track-SQL: Enhancing Generative Language Models with Dual-Extractive Modules for Schema and Context Tracking in Multi-turn Text-to-SQL
Bingfeng Chen, Shaobin Shi, Yongqi Luo +3
Generative language models have shown significant potential in single-turn Text-to-SQL. However, their performance does not extend equivalently to multi-turn Text-to-SQL. This is p…
What Gets Activated: Uncovering Domain and Driver Experts in MoE Language Models
Guimin Hu, Meng Li, Qiwei Peng +3
Most interpretability work focuses on layer- or neuron-level mechanisms in Transformers, leaving expert-level behavior in MoE LLMs underexplored. Motivated by functional specializa…