1 citations · 1 across the 9 of their papers we have counts for
9 papers
When LLM Meets Tree Search: A Systematic View of Inference as Search in Large Language Models
Jiaqi Wei, Xiang Zhang, Yuejin Yang +10
As pretraining scaling laws approach saturation, Test-Time Scaling (TTS) has emerged as an important direction for improving reasoning by allocating inference-time compute to a fix…
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…
AblateCell: A Reproduce-then-Ablate Agent for Virtual Cell Repositories
Xue Xia, Chengkai Yao, Mingyu Tsoi +10
Systematic ablations are essential to attribute performance gains in AI Virtual Cells, yet they are rarely performed because biological repositories are under-standardized and tigh…
HarmonyCell: Automating Single-Cell Perturbation Modeling under Semantic and Distribution Shifts
Wenxuan Huang, Mingyu Tsoi, Yanhao Huang +10
Single-cell perturbation studies face dual heterogeneity bottlenecks: (i) semantic heterogeneity--identical biological concepts encoded under incompatible metadata schemas across d…
Reflection Pretraining Enables Token-Level Self-Correction in Biological Sequence Models
Xiang Zhang, Jiaqi Wei, Yuejin Yang +8
Chain-of-Thought (CoT) prompting has significantly advanced task-solving capabilities in natural language processing with large language models. Unlike standard prompting, CoT enco…
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…
Unifying Tree Search Algorithm and Reward Design for LLM Reasoning: A Survey
Jiaqi Wei, Xiang Zhang, Yuejin Yang +10
Deliberative tree search is a cornerstone of modern Large Language Model (LLM) research, driving the pivot from brute-force scaling toward algorithmic efficiency. This single parad…
TimeSeriesScientist: A General-Purpose AI Agent for Time Series Analysis
Haokun Zhao, Xiang Zhang, Jiaqi Wei +4
Time series forecasting is central to decision-making in domains as diverse as energy, finance, climate, and public health. In practice, forecasters face thousands of short, noisy…
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…