6 citations · 7 across the 4 of their papers we have counts for
5 papers
NeuroSymb-MRG: Differentiable Abductive Reasoning with Active Uncertainty Minimization for Radiology Report Generation
Rong Fu, Yiqing Lyu, Chunlei Meng +9
Automatic generation of radiology reports seeks to reduce clinician workload while improving documentation consistency. Existing methods that adopt encoder-decoder or retrieval-aug…
\texttt{ReMind}: Understanding Deductive Code Reasoning in LLMs
Jun Gao, Yun Peng, Xiaoxue Ren
Large Language Models (LLMs) have achieved remarkable progress in code-related tasks. Despite their advancement, empirical evidence reveals that they still struggle with \emph{dedu…
LLM4Hint: Leveraging Large Language Models for Hint Recommendation in Offline Query Optimization
Suchen Liu, Jun Gao, Yinjun Han +1
Query optimization is essential for efficient SQL query execution in DBMS, and remains attractive over time due to the growth of data volumes and advances in hardware. Existing tra…
SelfCP: Compressing Over-Limit Prompt via the Frozen Large Language Model Itself
Jun Gao, Ziqiang Cao, Wenjie Li
Long prompt leads to huge hardware costs when using transformer-based Large Language Models (LLMs). Unfortunately, many tasks, such as summarization, inevitably introduce long docu…
WebCiteS: Attributed Query-Focused Summarization on Chinese Web Search Results with Citations
Haolin Deng, Chang Wang, Xin Li +6
Enhancing the attribution in large language models (LLMs) is a crucial task. One feasible approach is to enable LLMs to cite external sources that support their generations. Howeve…