1 citations · 1 across the 6 of their papers we have counts for
6 papers
When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning
Jiaqi Wei, Xuehang Guo, Pengfei Yu +5
In single-stream autoregressive interfaces, the same tokens both update the model state and constitute an irreversible public commitment. This coupling creates a silence tax: addit…
Semantic Manipulation Localization
Zhenshan Tan, Chenhan Lu, Yuxiang Huang +6
Image Manipulation Localization (IML) aims to identify edited regions in an image. However, with the increasing use of modern image editing and generative models, many manipulation…
FORESTLLM: Large Language Models Make Random Forest Great on Few-shot Tabular Learning
Zhihan Yang, Jiaqi Wei, Xiang Zhang +6
Tabular data high-stakes critical decision-making in domains such as finance, healthcare, and scientific discovery. Yet, learning effectively from tabular data in few-shot settings…
SlideGen: Collaborative Multimodal Agents for Scientific Slide Generation
Xin Liang, Zhilin Zhang, Xiang Zhang +4
Creating presentation slides from scientific papers is not simply a matter of summarizing paragraphs. A presenter is required to decide what story to tell, which figures and equati…
QuantHarness: Price-Driven Multi-Agent LLMs for High-Frequency Trading
Fei Xiong, Xiang Zhang, Aosong Feng +2
Recent advances in Large Language Models (LLMs) have shown remarkable capabilities in financial reasoning and market understanding. Multi-agent LLM frameworks such as TradingAgent…
PosterGen: Aesthetic-Aware Multi-Modal Paper-to-Poster Generation via Multi-Agent LLMs
Zhilin Zhang, Xiang Zhang, Jiaqi Wei +2
Multi-agent systems built upon large language models (LLMs) have demonstrated remarkable capabilities in tackling complex compositional tasks. In this work, we apply this paradigm…