2 citations · 7 across the 18 of their papers we have counts for
20 papers
The Sum of All Summaries: PROPALIGN for Graded Proposition Salience Evaluation
Lin Ai, Emma Thronson, Katherine Conhaim +1
Identification and ranking of salient propositions in documents is indirectly involved in many AI tasks, but few papers define proposition salience scores clearly, make diverse dat…
Using LMs to Model the Effects of Context and Coreference during Sentence Comprehension
Kohei Kajikawa, Lin Ai, Tatsuki Kuribayashi +1
Language models (LMs) are often used as a tool to model human language processing. Recent studies suggest that severely restricting LMs' context window improves their fit to human…
Rhythms of Work: Multi-Scale Interpretation of Human Behavioral Traces for Workplace Agents
Lin Ai, Scott Counts
Runtime traces are becoming a central substrate for understanding agentic systems, yet interpretation has focused largely on what the agent did. Workplace agents face the complemen…
An Interactive Paradigm for Deep Research
Lin Ai, Victor S. Bursztyn, Xiang Chen +2
Recent advances in large language models (LLMs) have enabled deep research systems that synthesize comprehensive, report-style answers to open-ended queries by combining retrieval,…
TeamFusion: Supporting Open-ended Teamwork with Multi-Agent Systems
Jiale Liu, Victor S. Bursztyn, Lin Ai +4
In open-ended domains, teams must reconcile diverse viewpoints to produce strong deliverables. Answer aggregation approaches commonly used in closed domains are ill-suited to this…
Detecting Mental Manipulation in Speech via Synthetic Multi-Speaker Dialogue
Run Chen, Wen Liang, Ziwei Gong +2
Mental manipulation, the strategic use of language to covertly influence or exploit others, is a newly emerging task in computational social reasoning. Prior work has focused exclu…
Learning More with Less: Self-Supervised Approaches for Low-Resource Speech Emotion Recognition
Ziwei Gong, Pengyuan Shi, Kaan Donbekci +5
Speech Emotion Recognition (SER) has seen significant progress with deep learning, yet remains challenging for Low-Resource Languages (LRLs) due to the scarcity of annotated data.…
A Review of Incorporating Psychological Theories in LLMs
Zizhou Liu, Ziwei Gong, Lin Ai +5
Psychological insights have long shaped pivotal NLP breakthroughs, from attention mechanisms to reinforcement learning and social modeling. As Large Language Models (LLMs) develop,…
Personalized Attacks of Social Engineering in Multi-turn Conversations: LLM Agents for Simulation and Detection
Tharindu Kumarage, Cameron Johnson, Jadie Adams +7
The rapid advancement of conversational agents, particularly chatbots powered by Large Language Models (LLMs), poses a significant risk of social engineering (SE) attacks on social…
Akan Cinematic Emotions (ACE): A Multimodal Multi-party Dataset for Emotion Recognition in Movie Dialogues
David Sasu, Zehui Wu, Ziwei Gong +5
In this paper, we introduce the Akan Conversation Emotion (ACE) dataset, the first multimodal emotion dialogue dataset for an African language, addressing the significant lack of r…
ToxiLab: How Well Do Open-Source LLMs Generate Synthetic Toxicity Data?
Zheng Hui, Zhaoxiao Guo, Hang Zhao +5
Effective toxic content detection relies heavily on high-quality and diverse data, which serve as the foundation for robust content moderation models. Synthetic data has become a c…
NovAScore: A New Automated Metric for Evaluating Document Level Novelty
Lin Ai, Ziwei Gong, Harshsaiprasad Deshpande +4
The rapid expansion of online content has intensified the issue of information redundancy, underscoring the need for solutions that can identify genuinely new information. Despite…
CREAM: Comparison-Based Reference-Free ELO-Ranked Automatic Evaluation for Meeting Summarization
Ziwei Gong, Lin Ai, Harshsaiprasad Deshpande +5
Large Language Models (LLMs) have spurred interest in automatic evaluation methods for summarization, offering a faster, more cost-effective alternative to human evaluation. Howeve…
PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent
Jiateng Liu, Lin Ai, Zizhou Liu +6
Propaganda plays a critical role in shaping public opinion and fueling disinformation. While existing research primarily focuses on identifying propaganda techniques, it lacks the…
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal Nuances
Zehui Wu, Ziwei Gong, Lin Ai +3
Emotion recognition in speech is a challenging multimodal task that requires understanding both verbal content and vocal nuances. This paper introduces a novel approach to emotion…
Defending Against Social Engineering Attacks in the Age of LLMs
Lin Ai, Tharindu Kumarage, Amrita Bhattacharjee +12
The proliferation of Large Language Models (LLMs) poses challenges in detecting and mitigating digital deception, as these models can emulate human conversational patterns and faci…
What Makes A Video Radicalizing? Identifying Sources of Influence in QAnon Videos
Lin Ai, Yu-Wen Chen, Yuwen Yu +3
In recent years, radicalization is being increasingly attempted on video-sharing platforms. Previous studies have been proposed to identify online radicalization using generic soci…
Enhancing Pre-Trained Generative Language Models with Question Attended Span Extraction on Machine Reading Comprehension
Lin Ai, Zheng Hui, Zizhou Liu +1
Machine Reading Comprehension (MRC) poses a significant challenge in the field of Natural Language Processing (NLP). While mainstream MRC methods predominantly leverage extractive…
QASE Enhanced PLMs: Improved Control in Text Generation for MRC
Lin Ai, Zheng Hui, Zizhou Liu +1
To address the challenges of out-of-control generation in generative models for machine reading comprehension (MRC), we introduce the Question-Attended Span Extraction (QASE) modul…
A Survey on Open Information Extraction from Rule-based Model to Large Language Model
Pai Liu, Wenyang Gao, Wenjie Dong +7
Open Information Extraction (OpenIE) represents a crucial NLP task aimed at deriving structured information from unstructured text, unrestricted by relation type or domain. This su…