1 citations · 2 across the 7 of their papers we have counts for
8 papers
STAGE: A Full-Screenplay Benchmark for Reasoning over Evolving Stories
Qiuyu Tian, Yiding Li, Yingce Xia +9
Movie screenplays are a demanding testbed for long-form narrative understanding, as characters' goals, beliefs, knowledge, and relationships evolve continuously across scenes. Howe…
CCrepairBench: A High-Fidelity Benchmark and Reinforcement Learning Framework for C++ Compilation Repair
Weixuan Sun, Jucai Zhai, Dengfeng Liu +6
The automated repair of C++ compilation errors presents a significant challenge, the resolution of which is critical for developer productivity. Progress in this domain is constrai…
GPU-Accelerated Belief Propagation for Program Analysis
Haoyu Feng, Xin Zhang
Belief Propagation (BP) is a widely used approximate inference algorithm in probabilistic graphical models (PGMs), but is computationally expensive when applied to large-scale prog…
LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generation
Chen-Chia Chang, Wan-Hsuan Lin, Yikang Shen +2
Automation of analog topology design is crucial due to customized requirements of modern applications with heavily manual engineering efforts. The state-of-the-art work applies a s…
TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data Synthesis
Xiaorui Wu, Xiaofeng Mao, Fei Li +5
Large Language Models (LLMs) excel in various natural language processing tasks but remain vulnerable to generating harmful content or being exploited for malicious purposes. Altho…
EVOREFUSE: Evolutionary Prompt Optimization for Evaluation and Mitigation of LLM Over-Refusal to Pseudo-Malicious Instructions
Xiaorui Wu, Fei Li, Xiaofeng Mao +6
Large language models (LLMs) frequently refuse to respond to pseudo-malicious instructions: semantically harmless input queries triggering unnecessary LLM refusals due to conservat…
CoT-RAG: Integrating Chain of Thought and Retrieval-Augmented Generation to Enhance Reasoning in Large Language Models
Feiyang Li, Peng Fang, Zhan Shi +5
Chain-of-thought (CoT) reasoning boosts large language models' (LLMs) performance on complex tasks but faces two key limitations: a lack of reliability when solely relying on LLM-g…
Enhancing Reasoning to Adapt Large Language Models for Domain-Specific Applications
Bo Wen, Xin Zhang
This paper presents SOLOMON, a novel Neuro-inspired Large Language Model (LLM) Reasoning Network architecture that enhances the adaptability of foundation models for domain-specifi…