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20242026
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cs.CL2026

MineExplorer: Evaluating Open-World Exploration of MLLM Agents in Minecraft

Tianjie Ju, Yueqing Sun, Zheng Wu +7

Multimodal large language models (MLLMs) have shown strong capabilities in perception, reasoning, and action generation. However, their ability to sustain exploration in dynamic op…

cs.CL2026

Beyond Fine-Tuning: In-Context Learning and Chain-of-Thought for Reasoned Distractor Generation

Elaf Alhazmi, Quan Z. Sheng, Wei Emma Zhang

Distractor generation (DG) remains a labor-intensive task that still significantly depends on domain experts. The task focuses on generating plausible yet incorrect options, known…

cs.CL2025

IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web

Hongcheng Guo, Wei Zhang, Junhao Chen +9

Recently advancements in large multimodal models have led to significant strides in image comprehension capabilities. Despite these advancements, there is a lack of the robust benc…

cs.CL2025

M3TQA: Massively Multilingual Multitask Table Question Answering

Daixin Shu, Jian Yang, Zhenhe Wu +11

Tabular data is a fundamental component of real-world information systems, yet most research in table understanding remains confined to English, leaving multilingual comprehension…

cs.CL2025

IFEvalCode: Controlled Code Generation

Jian Yang, Wei Zhang, Shukai Liu +9

Code large language models (Code LLMs) have made significant progress in code generation by translating natural language descriptions into functional code; however, real-world appl…

cs.CL2025

Multilingual Multimodal Software Developer for Code Generation

Linzheng Chai, Jian Yang, Shukai Liu +12

The rapid advancement of Large Language Models (LLMs) has significantly improved code generation, yet most models remain text-only, neglecting crucial visual aids like diagrams and…