4 papers
MMLongEmbed: Benchmarking Multimodal Embedding Models in Long-Context Scenarios
Haitian Wang, Ruoxi Sun, Quantong Qiu +5
Recent advancements have significantly expanded the theoretical context windows of Multimodal Embedding Models (MEMs). However, larger context windows do not necessarily translate…
Mechanistic Insights into Functional Sparsity in Multimodal LLMs via CoRe Heads
Ruoxi Sun, Quantong Qiu, Juntao Li +3
While Multimodal Large Language Models (MLLMs) demonstrate remarkable proficiency on complex vision-language tasks, the mechanisms by which they extract query-relevant visual featu…
MemoryRewardBench: Benchmarking Reward Models for Long-Term Memory Management in Large Language Models
Zecheng Tang, Baibei Ji, Ruoxi Sun +7
Existing works increasingly adopt memory-centric mechanisms to process long contexts in a segment manner, and effective memory management is one of the key capabilities that enable…
LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework
Zecheng Tang, Haitian Wang, Quantong Qiu +5
Long-context processing has become a fundamental capability for large language models~(LLMs). To assess model's long-context performance, numerous long-context evaluation benchmark…