8 citations · 18 across the 15 of their papers we have counts for
7 papers · 1 filter
GPT-2 Through the Lens of Vector Symbolic Architectures
Johannes Knittel, Tushaar Gangavarapu, Hendrik Strobelt +1
Understanding the general priniciples behind transformer models remains a complex endeavor. Experiments with probing and disentangling features using sparse autoencoders (SAE) sugg…
Understanding Graphical Perception in Data Visualization through Zero-shot Prompting of Vision-Language Models
Grace Guo, Jenna Jiayi Kang, Raj Sanjay Shah +2
Vision Language Models (VLMs) have been successful at many chart comprehension tasks that require attending to both the images of charts and their accompanying textual descriptions…
Task-Specific Directions: Definition, Exploration, and Utilization in Parameter Efficient Fine-Tuning
Chongjie Si, Zhiyi Shi, Shifan Zhang +3
Large language models demonstrate impressive performance on downstream tasks, yet they require extensive resource consumption when fully fine-tuning all parameters. To mitigate thi…
They're All Doctors: Synthesizing Diverse Counterfactuals to Mitigate Associative Bias
Salma Abdel Magid, Jui-Hsien Wang, Kushal Kafle +1
Vision Language Models (VLMs) such as CLIP are powerful models; however they can exhibit unwanted biases, making them less safe when deployed directly in applications such as text-…
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex
Spandan Madan, Will Xiao, Mingran Cao +3
We characterized the generalization capabilities of DNN-based encoding models when predicting neuronal responses from the visual cortex. We collected \textit{MacaqueITBench}, a lar…
Measuring and Controlling Instruction (In)Stability in Language Model Dialogs
Kenneth Li, Tianle Liu, Naomi Bashkansky +4
System-prompting is a standard tool for customizing language-model chatbots, enabling them to follow a specific instruction. An implicit assumption in the use of system prompts is…
The Indoor-Training Effect: unexpected gains from distribution shifts in the transition function
Serena Bono, Spandan Madan, Ishaan Grover +4
Is it better to perform tennis training in a pristine indoor environment or a noisy outdoor one? To model this problem, here we investigate whether shifts in the transition probabi…