8 citations · 16 across the 8 of their papers we have counts for
8 papers
Your thoughts tell who you are: Characterize the reasoning patterns of LRMs
Yida Chen, Yuning Mao, Xianjun Yang +7
Current comparisons of large reasoning models (LRMs) focus on macro-level statistics such as task accuracy or reasoning length. Whether different LRMs reason differently remains an…
When Bad Data Leads to Good Models
Kenneth Li, Yida Chen, Fernanda Viégas +1
In large language model (LLM) pretraining, data quality is believed to determine model quality. In this paper, we re-examine the notion of "quality" from the perspective of pre- an…
ChatGPT Doesn't Trust Chargers Fans: Guardrail Sensitivity in Context
Victoria R. Li, Yida Chen, Naomi Saphra
While the biases of language models in production are extensively documented, the biases of their guardrails have been neglected. This paper studies how contextual information abou…
Designing a Dashboard for Transparency and Control of Conversational AI
Yida Chen, Aoyu Wu, Trevor DePodesta +9
Conversational LLMs function as black box systems, leaving users guessing about why they see the output they do. This lack of transparency is potentially problematic, especially gi…
More than Correlation: Do Large Language Models Learn Causal Representations of Space?
Yida Chen, Yixian Gan, Sijia Li +2
Recent work found high mutual information between the learned representations of large language models (LLMs) and the geospatial property of its input, hinting an emergent internal…
Soil Image Segmentation Based on Mask R-CNN
Yida Chen, Kang Liu, Yi Xin +1
The complex background in the soil image collected in the field natural environment will affect the subsequent soil image recognition based on machine vision. Segmenting the soil c…
Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model
Yida Chen, Fernanda Viégas, Martin Wattenberg
Latent diffusion models (LDMs) exhibit an impressive ability to produce realistic images, yet the inner workings of these models remain mysterious. Even when trained purely on imag…
AttentionViz: A Global View of Transformer Attention
Catherine Yeh, Yida Chen, Aoyu Wu +3
Transformer models are revolutionizing machine learning, but their inner workings remain mysterious. In this work, we present a new visualization technique designed to help researc…