1 citations · 1 across the 5 of their papers we have counts for
5 papers
ToM: Leveraging Tree-oriented MapReduce for Long-Context Reasoning in Large Language Models
Jiani Guo, Zuchao Li, Jie Wu +5
Large Language Models (LLMs), constrained by limited context windows, often face significant performance degradation when reasoning over long contexts. To address this, Retrieval-A…
From Parameters to Performance: A Data-Driven Study on LLM Structure and Development
Suqing Wang, Zuchao Li, Luohe Shi +4
Large language models (LLMs) have achieved remarkable success across various domains, driving significant technological advancements and innovations. Despite the rapid growth in mo…
CoViPAL: Layer-wise Contextualized Visual Token Pruning for Large Vision-Language Models
Zicong Tang, Ziyang Ma, Suqing Wang +5
Large Vision-Language Models (LVLMs) process multimodal inputs consisting of text tokens and vision tokens extracted from images or videos. Due to the rich visual information, a si…
When Disagreements Elicit Robustness: Investigating Self-Repair Capabilities under LLM Multi-Agent Disagreements
Tianjie Ju, Bowen Wang, Hao Fei +9
Recent advances in Large Language Models (LLMs) have upgraded them from sophisticated text generators to autonomous agents capable of cooperation and tool use in multi-agent system…
Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data
Dehai Min, Nan Hu, Rihui Jin +8
Augmenting Large Language Models (LLMs) for Question Answering (QA) with domain specific data has attracted wide attention. However, domain data often exists in a hybrid format, in…