3 papers
cs.AI2026
Agentic-MME: What Agentic Capability Really Brings to Multimodal Intelligence?
Qianshan Wei, Yishan Yang, Siyi Wang +12
Multimodal Large Language Models (MLLMs) are evolving from passive observers into active agents, solving problems through Visual Expansion (invoking visual tools) and Knowledge Exp…
cs.SE2025
Decompile-Bench: Million-Scale Binary-Source Function Pairs for Real-World Binary Decompilation
Hanzhuo Tan, Xiaolong Tian, Hanrui Qi +6
Recent advances in LLM-based decompilers have been shown effective to convert low-level binaries into human-readable source code. However, there still lacks a comprehensive benchma…
cs.SE2025
SK2Decompile: LLM-based Two-Phase Binary Decompilation from Skeleton to Skin
Hanzhuo Tan, Weihao Li, Xiaolong Tian +4
Large Language Models (LLMs) have emerged as a promising approach for binary decompilation. However, the existing LLM-based decompilers still are somewhat limited in effectively pr…