activity
20232026
most citedFaiMA: Feature-aware In-context Learning for Multi-domain Aspect-based Sentiment Analysis

4 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

P1-VL: Bridging Visual Perception and Scientific Reasoning in Physics Olympiads

Yun Luo, Futing Wang, Qianjia Cheng +28

The transition from symbolic manipulation to science-grade reasoning represents a pivotal frontier for Large Language Models (LLMs), with physics serving as the critical test ancho…

cs.AI2025

Jupiter: Enhancing LLM Data Analysis Capabilities via Notebook and Inference-Time Value-Guided Search

Shuocheng Li, Yihao Liu, Silin Du +7

Large language models (LLMs) have shown great promise in automating data science workflows, but existing models still struggle with multi-step reasoning and tool use, which limits…

cs.CL2024★ 4 cited

FaiMA: Feature-aware In-context Learning for Multi-domain Aspect-based Sentiment Analysis

Songhua Yang, Xinke Jiang, Hanjie Zhao +3

Multi-domain aspect-based sentiment analysis (ABSA) seeks to capture fine-grained sentiment across diverse domains. While existing research narrowly focuses on single-domain applic…

cs.CL2024★ 3 cited

Kuaiji: the First Chinese Accounting Large Language Model

Jiayuan Luo, Songhua Yang, Xiaoling Qiu +5

Large Language Models (LLMs) like ChatGPT and GPT-4 have demonstrated impressive proficiency in comprehending and generating natural language. However, they encounter difficulties…

cs.CL2024

ASGEA: Exploiting Logic Rules from Align-Subgraphs for Entity Alignment

Yangyifei Luo, Zhuo Chen, Lingbing Guo +4

Entity alignment (EA) aims to identify entities across different knowledge graphs that represent the same real-world objects. Recent embedding-based EA methods have achieved state-…

cs.RO2023★ 3 cited

BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous Driving

Haicheng Liao, Zhenning Li, Huanming Shen +5

The ability to accurately predict the trajectory of surrounding vehicles is a critical hurdle to overcome on the journey to fully autonomous vehicles. To address this challenge, we…