3 citations · 7 across the 5 of their papers we have counts for
5 papers
SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals
Ruihan Yang, Jiangjie Chen, Yikai Zhang +5
Language agents powered by large language models (LLMs) are increasingly valuable as decision-making tools in domains such as gaming and programming. However, these agents often fa…
Wings: Learning Multimodal LLMs without Text-only Forgetting
Yi-Kai Zhang, Shiyin Lu, Yang Li +7
Multimodal large language models (MLLMs), initiated with a trained LLM, first align images with text and then fine-tune on multimodal mixed inputs. However, the MLLM catastrophical…
TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation
Yikai Zhang, Siyu Yuan, Caiyu Hu +3
Despite remarkable advancements in emulating human-like behavior through Large Language Models (LLMs), current textual simulations do not adequately address the notion of time. To…
Learning to Abstain From Uninformative Data
Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard +5
Learning and decision-making in domains with naturally high noise-to-signal ratio, such as Finance or Healthcare, is often challenging, while the stakes are very high. In this pape…
Learning to Segment from Noisy Annotations: A Spatial Correction Approach
Jiachen Yao, Yikai Zhang, Songzhu Zheng +3
Noisy labels can significantly affect the performance of deep neural networks (DNNs). In medical image segmentation tasks, annotations are error-prone due to the high demand in ann…