8 papers
FIDES: Faithful Inference via Deep Evidence Signals for Retrieval-Memory Conflict in RAG
Zhe Yu, Wenpeng Xing, Tiancheng Zhao +3
When retrieved evidence contradicts parametric memory, language models frequently ignore context and default to memorized priors -- a failure that undermines the core purpose of re…
Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression
Zilun Zhang, Yutao Sun, Tiancheng Zhao +4
Humans can retain old knowledge while learning new information, but Large Language Models (LLMs) often suffer from catastrophic forgetting when post-pretrained or supervised fine-t…
Unifying Language Agent Algorithms with Graph-based Orchestration Engine for Reproducible Agent Research
Qianqian Zhang, Jiajia Liao, Heting Ying +9
Language agents powered by large language models (LLMs) have demonstrated remarkable capabilities in understanding, reasoning, and executing complex tasks. However, developing robu…
ImageRAG: Enhancing Ultra High Resolution Remote Sensing Imagery Analysis with ImageRAG
Zilun Zhang, Haozhan Shen, Tiancheng Zhao +7
Ultra High Resolution (UHR) remote sensing imagery (RSI) (e.g. 100,000 100,000 pixels or more) poses a significant challenge for current Remote Sensing Multimodal Large La…
HORAE: A Domain-Agnostic Language for Automated Service Regulation
Yutao Sun, Mingshuai Chen, Tiancheng Zhao +8
Artificial intelligence is rapidly encroaching on the field of service regulation. However, existing AI-based regulation techniques are often tailored to specific application domai…
VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model
Haozhan Shen, Peng Liu, Jingcheng Li +9
Recently DeepSeek R1 has shown that reinforcement learning (RL) can substantially improve the reasoning capabilities of Large Language Models (LLMs) through a simple yet effective…