6 citations · 11 across the 9 of their papers we have counts for
9 papers
Probability of Root Cause: A Counterfactual Definition and Its Identification
Zitong Lu, Zhi Geng, Wei Li +1
Attributing an observed outcome to its root cause is a central task in domains ranging from medical diagnosis to engineering fault diagnosis. Existing approaches either equate the…
Do VLMs Align Better with Humans than LLMs during Natural Reading?
Jinzhou Wu, Zhengwu Ma, Jixing Li +2
Large language models have become increasingly useful computational models of human language processing, but it remains open whether vision-language learning makes text representat…
ScholarEval: Research Idea Evaluation Grounded in Literature
Hanane Nour Moussa, Patrick Queiroz Da Silva, Daniel Adu-Ampratwum +7
As AI tools become increasingly common for research ideation, robust evaluation is critical to ensure the validity and usefulness of generated ideas. We introduce ScholarEval, a re…
AutoSDT: Scaling Data-Driven Discovery Tasks Toward Open Co-Scientists
Yifei Li, Hanane Nour Moussa, Ziru Chen +16
Despite long-standing efforts in accelerating scientific discovery with AI, building AI co-scientists remains challenging due to limited high-quality data for training and evaluati…
Language learning shapes visual category-selectivity in deep neural networks
Zitong Lu, Yuxin Wang
Category-selective regions in the human brain-such as the fusiform face area (FFA), extrastriate body area (EBA), parahippocampal place area (PPA), and visual word form area (VWFA)…
ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
Ziru Chen, Shijie Chen, Yuting Ning +17
The advancements of large language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked…
Teaching CORnet Human fMRI Representations for Enhanced Model-Brain Alignment
Zitong Lu, Yile Wang
Deep convolutional neural networks (DCNNs) have demonstrated excellent performance in object recognition and have been found to share some similarities with brain visual processing…
Achieving More Human Brain-Like Vision via Human EEG Representational Alignment
Zitong Lu, Yile Wang, Julie D. Golomb
Despite advancements in artificial intelligence, object recognition models still lag behind in emulating visual information processing in human brains. Recent studies have highligh…
Generate your neural signals from mine: individual-to-individual EEG converters
Zitong Lu, Julie D. Golomb
Most models in cognitive and computational neuroscience trained on one subject do not generalize to other subjects due to individual differences. An ideal individual-to-individual…