134 citations · 706 across the 103 of their papers we have counts for
13 papers · 1 filter
Achieving Domain-Independent Certified Robustness via Knowledge Continuity
Alan Sun, Chiyu Ma, Kenneth Ge +1
We present knowledge continuity, a novel definition inspired by Lipschitz continuity which aims to certify the robustness of neural networks across input domains (such as continuou…
ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Sentence
Yuxin Wang, Xiaomeng Zhu, Weimin Lyu +2
Handling implicit language is essential for natural language processing systems to achieve precise text understanding and facilitate natural interactions with users. Despite its im…
On the Exploration of LM-Based Soft Modular Robot Design
Weicheng Ma, Luyang Zhao, Chun-Yi She +5
Recent large language models (LLMs) have demonstrated promising capabilities in modeling real-world knowledge and enhancing knowledge-based generation tasks. In this paper, we furt…
Interpretable Image Classification with Adaptive Prototype-based Vision Transformers
Chiyu Ma, Jon Donnelly, Wenjun Liu +3
We present ProtoViT, a method for interpretable image classification combining deep learning and case-based reasoning. This method classifies an image by comparing it to a set of l…
The Computational Anatomy of Humility: Modeling Intellectual Humility in Online Public Discourse
Xiaobo Guo, Neil Potnis, Melody Yu +2
The ability for individuals to constructively engage with one another across lines of difference is a critical feature of a healthy pluralistic society. This is also true in online…
AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality
Peijun Qing, Chongyang Gao, Yefan Zhou +3
Parameter-efficient fine-tuning methods, such as Low-Rank Adaptation (LoRA), are known to enhance training efficiency in Large Language Models (LLMs). Due to the limited parameters…
Enhanced Detection of Conversational Mental Manipulation Through Advanced Prompting Techniques
Ivory Yang, Xiaobo Guo, Sean Xie +1
This study presents a comprehensive, long-term project to explore the effectiveness of various prompting techniques in detecting dialogical mental manipulation. We implement Chain-…
Semantic Compositions Enhance Vision-Language Contrastive Learning
Maxwell Aladago, Lorenzo Torresani, Soroush Vosoughi
In the field of vision-language contrastive learning, models such as CLIP capitalize on matched image-caption pairs as positive examples and leverage within-batch non-matching pair…
Serial Position Effects of Large Language Models
Xiaobo Guo, Soroush Vosoughi
Large Language Models (LLMs) have shown remarkable capabilities in zero-shot learning applications, generating responses to queries using only pre-training information without the…
MODABS: Multi-Objective Learning for Dynamic Aspect-Based Summarization
Xiaobo Guo, Soroush Vosoughi
The rapid proliferation of online content necessitates effective summarization methods, among which dynamic aspect-based summarization stands out. Unlike its traditional counterpar…
Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-Judge
Lin Shi, Chiyu Ma, Wenhua Liang +3
LLM-as-a-Judge has emerged as a promising alternative to human evaluators across various tasks, yet inherent biases - particularly position bias, the tendency to favor solutions ba…
MentalManip: A Dataset For Fine-grained Analysis of Mental Manipulation in Conversations
Yuxin Wang, Ivory Yang, Saeed Hassanpour +1
Mental manipulation, a significant form of abuse in interpersonal conversations, presents a challenge to identify due to its context-dependent and often subtle nature. The detectio…
Disordered-DABS: A Benchmark for Dynamic Aspect-Based Summarization in Disordered Texts
Xiaobo Guo, Soroush Vosoughi
Aspect-based summarization has seen significant advancements, especially in structured text. Yet, summarizing disordered, large-scale texts, like those found in social media and cu…