6 papers
From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
Qirui Zheng, Xingbo Wang, Keyuan Cheng +5
The advent of artificial intelligence has propelled AI-Generated Game Commentary (AI-GGC) into a rapidly expanding research area, offering advantages such as scalable availability…
BotzoneBench: Scalable LLM Evaluation via Graded AI Anchors
Lingfeng Li, Yunlong Lu, Yuefei Zhang +7
Large Language Models (LLMs) are increasingly deployed in interactive environments requiring strategic decision-making, yet systematic evaluation of these capabilities remains chal…
COMPKE: Complex Question Answering under Knowledge Editing
Keyuan Cheng, Zijian Kan, Zhixian He +5
Knowledge Editing, which efficiently modifies the knowledge in large language models, has gathered great attention. Current benchmarks primarily use multi-hop question answering to…
CODEMENV: Benchmarking Large Language Models on Code Migration
Keyuan Cheng, Xudong Shen, Yihao Yang +6
Large language models (LLMs) have shown remarkable capabilities across various software engineering tasks; however, their effectiveness in code migration, adapting code to run in d…
Code-Vision: Evaluating Multimodal LLMs Logic Understanding and Code Generation Capabilities
Hanbin Wang, Xiaoxuan Zhou, Zhipeng Xu +7
This paper introduces Code-Vision, a benchmark designed to evaluate the logical understanding and code generation capabilities of Multimodal Large Language Models (MLLMs). It chall…
Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing
Zhuoran Zhang, Yongxiang Li, Zijian Kan +3
The locate-then-edit paradigm has shown significant promise for knowledge editing (KE) in Large Language Models (LLMs). While previous methods perform well on single-hop fact recal…