3 citations · 8 across the 8 of their papers we have counts for
8 papers
Vision Token Reduction via Attention-Driven Self-Compression for Efficient Multimodal Large Language Models
Omer Faruk Deniz, Ruiyu Mao, Ruochen Li +2
Multimodal Large Language Models (MLLMs) incur significant computational cost from processing numerous vision tokens through all LLM layers. Prior pruning methods operate either be…
The Ramon Llull's Thinking Machine for Automated Ideation
Xinran Zhao, Boyuan Zheng, Chenglei Si +8
This paper revisits Ramon Llull's Ars combinatoria - a medieval framework for generating knowledge through symbolic recombination - as a conceptual foundation for building a modern…
Coherent Multimodal Reasoning with Iterative Self-Evaluation for Vision-Language Models
Wenjie Luo, Ruocheng Li, Shanshan Zhu +1
Despite significant advancements, current large language models (LLMs) and vision-language models (LVLMs) continue to struggle with complex, multi-step, cross-modal common sense re…
LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling Research
Shuo Yan, Ruochen Li, Ziming Luo +11
Large language model (LLM) agents have demonstrated remarkable potential in advancing scientific discovery. However, their capability in the fundamental yet crucial task of reprodu…
AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control
Ruosen Li, Ziming Luo, Quan Zhang +4
Large reasoning models (LRMs) achieve impressive reasoning capabilities by generating lengthy chain-of-thoughts, but this "overthinking" incurs high latency and cost without commen…
LDC: Learning to Generate Research Idea with Dynamic Control
Ruochen Li, Liqiang Jing, Chi Han +2
Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing approaches primarily focus on prompti…
MLR-Copilot: Autonomous Machine Learning Research based on Large Language Models Agents
Ruochen Li, Teerth Patel, Qingyun Wang +1
Autonomous machine learning research has gained significant attention recently. We present MLR-COPILOT, an autonomous Machine Learning Research framework powered by large language…
IQA-EVAL: Automatic Evaluation of Human-Model Interactive Question Answering
Ruosen Li, Ruochen Li, Barry Wang +1
To evaluate Large Language Models (LLMs) for question answering (QA), traditional methods typically focus on assessing single-turn responses to given questions. However, this appro…