1 citations · 1 across the 9 of their papers we have counts for
9 papers
Adaptive Multi-Stage Patent Claim Generation with Unified Quality Assessment
Chen-Wei Liang, Bin Guo, Zhen-Yuan Wei +1
Current patent claim generation systems face three fundamental limitations: poor cross-jurisdictional generalization, inadequate semantic relationship modeling between claims and p…
Taxonomy-based Negative Sampling In Personalized Semantic Search for E-commerce
Uthman Jinadu, Siawpeng Er, Le Yu +4
Large retail outlets offer products that may be domain-specific, and this requires having a model that can understand subtle differences in similar items. Sampling techniques used…
SwarmSys: Decentralized Swarm-Inspired Agents for Scalable and Adaptive Reasoning
Ruohao Li, Hongjun Liu, Leyi Zhao +7
Large language model (LLM) agents have shown remarkable reasoning abilities. However, existing multi-agent frameworks often rely on fixed roles or centralized control, limiting sca…
Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics
Lianhao Zhou, Hongyi Ling, Cong Fu +14
Computing has long served as a cornerstone of scientific discovery. Recently, a paradigm shift has emerged with the rise of large language models (LLMs), introducing autonomous sys…
LLM-Explorer: Towards Efficient and Affordable LLM-based Exploration for Mobile Apps
Shanhui Zhao, Hao Wen, Wenjie Du +5
Large language models (LLMs) have opened new opportunities for automated mobile app exploration, an important and challenging problem that used to suffer from the difficulty of gen…
Event Argument Extraction with Enriched Prompts
Chen Liang
This work aims to delve deeper into prompt-based event argument extraction (EAE) models. We explore the impact of incorporating various types of information into the prompt on mode…
Precise Drive with VLM: First Prize Solution for PRCV 2024 Drive LM challenge
Bin Huang, Siyu Wang, Yuanpeng Chen +8
This technical report outlines the methodologies we applied for the PRCV Challenge, focusing on cognition and decision-making in driving scenarios. We employed InternVL-2.0, a pion…
Textualized Agent-Style Reasoning for Complex Tasks by Multiple Round LLM Generation
Chen Liang, Zhifan Feng, Zihe Liu +4
Chain-of-thought prompting significantly boosts the reasoning ability of large language models but still faces three issues: hallucination problem, restricted interpretability, and…
Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy
Yao Zhao, Zhitian Xie, Chen Liang +2
As Large Language Models (LLMs) have made significant advancements across various tasks, such as question answering, translation, text summarization, and dialogue systems, the need…