62 citations · 430 across the 52 of their papers we have counts for
52 papers
Identifying and Mitigating the Security Risks of Generative AI
Clark Barrett, Brad Boyd, Elie Burzstein +20
Every major technical invention resurfaces the dual-use dilemma -- the new technology has the potential to be used for good as well as for harm. Generative AI (GenAI) techniques, s…
Shaping the Emerging Norms of Using Large Language Models in Social Computing Research
Hong Shen, Tianshi Li, Toby Jia-Jun Li +2
The emergence of Large Language Models (LLMs) has brought both excitement and concerns to social computing research. On the one hand, LLMs offer unprecedented capabilities in analy…
Modeling Cross-Cultural Pragmatic Inference with Codenames Duet
Omar Shaikh, Caleb Ziems, William Held +3
Pragmatic reference enables efficient interpersonal communication. Prior work uses simple reference games to test models of pragmatic reasoning, often with unidentified speakers an…
LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding
Yanzhe Zhang, Ruiyi Zhang, Jiuxiang Gu +4
Instruction tuning unlocks the superior capability of Large Language Models (LLM) to interact with humans. Furthermore, recent instruction-following datasets include images as visu…
TADA: Task-Agnostic Dialect Adapters for English
Will Held, Caleb Ziems, Diyi Yang
Large Language Models, the dominant starting point for Natural Language Processing (NLP) applications, fail at a higher rate for speakers of English dialects other than Standard Am…
Forgotten Knowledge: Examining the Citational Amnesia in NLP
Janvijay Singh, Mukund Rungta, Diyi Yang +1
Citing papers is the primary method through which modern scientific writing discusses and builds on past work. Collectively, citing a diverse set of papers (in time and area of stu…
NormBank: A Knowledge Bank of Situational Social Norms
Caleb Ziems, Jane Dwivedi-Yu, Yi-Chia Wang +2
We present NormBank, a knowledge bank of 155k situational norms. This resource is designed to ground flexible normative reasoning for interactive, assistive, and collaborative AI s…
Benchmarking Machine Translation with Cultural Awareness
Binwei Yao, Ming Jiang, Tara Bobinac +2
Translating culture-related content is vital for effective cross-cultural communication. However, many culture-specific items (CSIs) often lack viable translations across languages…
DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic Rules
Yanchen Liu, William Held, Diyi Yang
Existing large language models (LLMs) that mainly focus on Standard American English (SAE) often lead to significantly worse performance when being applied to other English dialect…
Can Large Language Models Transform Computational Social Science?
Caleb Ziems, William Held, Omar Shaikh +3
Large Language Models (LLMs) are capable of successfully performing many language processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify a…
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
Anya Belz, Craig Thomson, Ehud Reiter +39
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/le…
A Cheaper and Better Diffusion Language Model with Soft-Masked Noise
Jiaao Chen, Aston Zhang, Mu Li +2
Diffusion models that are based on iterative denoising have been recently proposed and leveraged in various generation tasks like image generation. Whereas, as a way inherently bui…
Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints
Albert Lu, Hongxin Zhang, Yanzhe Zhang +2
The limits of open-ended generative models are unclear, yet increasingly important. What causes them to succeed and what causes them to fail? In this paper, we take a prompt-centri…
Auditing Gender Presentation Differences in Text-to-Image Models
Yanzhe Zhang, Lu Jiang, Greg Turk +1
Text-to-image models, which can generate high-quality images based on textual input, have recently enabled various content-creation tools. Despite significantly affecting a wide ra…
Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang +3
Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot -- i.e., with…
Parameter-Efficient Fine-Tuning Design Spaces
Jiaao Chen, Aston Zhang, Xingjian Shi +3
Parameter-efficient fine-tuning aims to achieve performance comparable to fine-tuning, using fewer trainable parameters. Several strategies (e.g., Adapters, prefix tuning, BitFit,…
Just Another Day on Twitter: A Complete 24 Hours of Twitter Data
Juergen Pfeffer, Daniel Matter, Kokil Jaidka +13
At the end of October 2022, Elon Musk concluded his acquisition of Twitter. In the weeks and months before that, several questions were publicly discussed that were not only of int…
Human-in-the-loop Abstractive Dialogue Summarization
Jiaao Chen, Mohan Dodda, Diyi Yang
Abstractive dialogue summarization has received increasing attention recently. Despite the fact that most of the current dialogue summarization systems are trained to maximize the…
On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning
Omar Shaikh, Hongxin Zhang, William Held +2
Generating a Chain of Thought (CoT) has been shown to consistently improve large language model (LLM) performance on a wide range of NLP tasks. However, prior work has mainly focus…
DAMP: Doubly Aligned Multilingual Parser for Task-Oriented Dialogue
William Held, Christopher Hidey, Fei Liu +4
Modern virtual assistants use internal semantic parsing engines to convert user utterances to actionable commands. However, prior work has demonstrated that semantic parsing is a d…
Multi-VALUE: A Framework for Cross-Dialectal English NLP
Caleb Ziems, William Held, Jingfeng Yang +3
Dialect differences caused by regional, social, and economic factors cause performance discrepancies for many groups of language technology users. Inclusive and equitable language…
ConStruct-VL: Data-Free Continual Structured VL Concepts Learning
James Seale Smith, Paola Cascante-Bonilla, Assaf Arbelle +7
Recently, large-scale pre-trained Vision-and-Language (VL) foundation models have demonstrated remarkable capabilities in many zero-shot downstream tasks, achieving competitive res…
WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domain
Raj Sanjay Shah, Kunal Chawla, Dheeraj Eidnani +7
Pre-trained language models have shown impressive performance on a variety of tasks and domains. Previous research on financial language models usually employs a generic training s…
Geographic Citation Gaps in NLP Research
Mukund Rungta, Janvijay Singh, Saif M. Mohammad +1
In a fair world, people have equitable opportunities to education, to conduct scientific research, to publish, and to get credit for their work, regardless of where they live. Howe…