24 citations · 46 across the 16 of their papers we have counts for
15 papers · 1 filter
SERL-SQL: Selective Hindsight Distillation for Text-to-SQL Reinforcement Agentic Learning
Tao Liu, Tao Feng, Xiangheng Li +9
Recent Text-to-SQL systems increasingly rely on multi-turn interaction, execution feedback, and reinforcement learning. However, most existing methods use execution correctness onl…
AttnLink: Turning Attention into Schema Links for Text-to-SQL
Jinwang Song, Tao Liu, Haowen Zheng +3
Schema linking is a critical component of Text-to-SQL systems, but existing approaches often trade off contextual modeling capacity, score-based controllability, and inference effi…
IESR:Efficient MCTS-Based Modular Reasoning for Text-to-SQL with Large Language Models
Tao Liu, Jiafan Lu, Bohan Yu +11
Text-to-SQL is a key natural language processing task that maps natural language questions to SQL queries, enabling intuitive interaction with web-based databases. Although current…
BiasFilter: An Inference-Time Debiasing Framework for Large Language Models
Xiaoqing Cheng, Ruizhe Chen, Hongying Zan +2
Mitigating social bias in large language models (LLMs) has become an increasingly important research objective. However, existing debiasing methods often incur high human and compu…
LogicCat: A Chain-of-Thought Text-to-SQL Benchmark for Complex Reasoning
Tao Liu, Xutao Mao, Hongying Zan +12
Text-to-SQL is a critical task in natural language processing that aims to transform natural language questions into accurate and executable SQL queries. In real-world scenarios, t…
JOLT-SQL: Joint Loss Tuning of Text-to-SQL with Confusion-aware Noisy Schema Sampling
Jinwang Song, Hongying Zan, Kunli Zhang +4
Text-to-SQL, which maps natural language to SQL queries, has benefited greatly from recent advances in Large Language Models (LLMs). While LLMs offer various paradigms for this tas…
SILC-EFSA: Self-aware In-context Learning Correction for Entity-level Financial Sentiment Analysis
Senbin Zhu, Chenyuan He, Hongde Liu +6
In recent years, fine-grained sentiment analysis in finance has gained significant attention, but the scarcity of entity-level datasets remains a key challenge. To address this, we…
ZZU-NLP at SIGHAN-2024 dimABSA Task: Aspect-Based Sentiment Analysis with Coarse-to-Fine In-context Learning
Senbin Zhu, Hanjie Zhao, Xingren Wang +3
The DimABSA task requires fine-grained sentiment intensity prediction for restaurant reviews, including scores for Valence and Arousal dimensions for each Aspect Term. In this stud…
MRC-based Nested Medical NER with Co-prediction and Adaptive Pre-training
Xiaojing Du, Hanjie Zhao, Danyan Xing +2
In medical information extraction, medical Named Entity Recognition (NER) is indispensable, playing a crucial role in developing medical knowledge graphs, enhancing medical questio…
OpenEval: Benchmarking Chinese LLMs across Capability, Alignment and Safety
Chuang Liu, Linhao Yu, Jiaxuan Li +11
The rapid development of Chinese large language models (LLMs) poses big challenges for efficient LLM evaluation. While current initiatives have introduced new benchmarks or evaluat…
A Corpus for Named Entity Recognition in Chinese Novels with Multi-genres
Hanjie Zhao, Jinge Xie, Yuchen Yan +3
Entities like person, location, organization are important for literary text analysis. The lack of annotated data hinders the progress of named entity recognition (NER) in literary…
Zhongjing: Enhancing the Chinese Medical Capabilities of Large Language Model through Expert Feedback and Real-world Multi-turn Dialogue
Songhua Yang, Hanjie Zhao, Senbin Zhu +4
Recent advances in Large Language Models (LLMs) have achieved remarkable breakthroughs in understanding and responding to user intents. However, their performance lag behind genera…
Optimizing Deep Transformers for Chinese-Thai Low-Resource Translation
Wenjie Hao, Hongfei Xu, Lingling Mu +1
In this paper, we study the use of deep Transformer translation model for the CCMT 2022 Chinese-Thai low-resource machine translation task. We first explore the experiment settings…
NAPG: Non-Autoregressive Program Generation for Hybrid Tabular-Textual Question Answering
Tengxun Zhang, Hongfei Xu, Josef van Genabith +2
Hybrid tabular-textual question answering (QA) requires reasoning from heterogeneous information, and the types of reasoning are mainly divided into numerical reasoning and span ex…
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Ningyu Zhang, Mosha Chen, Zhen Bi +20
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice. With the development of biomedical langua…