71 citations · 177 across the 26 of their papers we have counts for
29 papers
A Curious Class of Adpositional Multiword Expressions in Korean
Junghyun Min, Na-Rae Han, Jena D. Hwang +1
Multiword expressions (MWEs) have been widely studied in cross-lingual annotation frameworks such as PARSEME. However, Korean MWEs remain underrepresented in these efforts. In part…
Ai2 Scholar QA: Organized Literature Synthesis with Attribution
Amanpreet Singh, Joseph Chee Chang, Chloe Anastasiades +15
Retrieval-augmented generation is increasingly effective in answering scientific questions from literature, but many state-of-the-art systems are expensive and closed-source. We in…
UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations
Wenting Zhao, Justin T Chiu, Jena D. Hwang +6
Language technologies that accurately model the dynamics of events must perform commonsense reasoning. Existing work evaluating commonsense reasoning focuses on making inferences a…
The Generative AI Paradox: "What It Can Create, It May Not Understand"
Peter West, Ximing Lu, Nouha Dziri +11
The recent wave of generative AI has sparked unprecedented global attention, with both excitement and concern over potentially superhuman levels of artificial intelligence: models…
"You Are An Expert Linguistic Annotator": Limits of LLMs as Analyzers of Abstract Meaning Representation
Allyson Ettinger, Jena D. Hwang, Valentina Pyatkin +2
Large language models (LLMs) show amazing proficiency and fluency in the use of language. Does this mean that they have also acquired insightful linguistic knowledge about the lang…
Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties
Taylor Sorensen, Liwei Jiang, Jena Hwang +10
Human values are crucial to human decision-making. Value pluralism is the view that multiple correct values may be held in tension with one another (e.g., when considering lying to…
COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statements
Xuhui Zhou, Hao Zhu, Akhila Yerukola +4
Warning: This paper contains content that may be offensive or upsetting. Understanding the harms and offensiveness of statements requires reasoning about the social and situational…
PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin +7
Procedural planning, which entails decomposing a high-level goal into a sequence of temporally ordered steps, is an important yet intricate task for machines. It involves integrati…
Faith and Fate: Limits of Transformers on Compositionality
Nouha Dziri, Ximing Lu, Melanie Sclar +13
Transformer large language models (LLMs) have sparked admiration for their exceptional performance on tasks that demand intricate multi-step reasoning. Yet, these models simultaneo…
Causal schema induction for knowledge discovery
Michael Regan, Jena D. Hwang, Keisuke Sakaguchi +1
Making sense of familiar yet new situations typically involves making generalizations about causal schemas, stories that help humans reason about event sequences. Reasoning about e…
ClarifyDelphi: Reinforced Clarification Questions with Defeasibility Rewards for Social and Moral Situations
Valentina Pyatkin, Jena D. Hwang, Vivek Srikumar +4
Context is everything, even in commonsense moral reasoning. Changing contexts can flip the moral judgment of an action; "Lying to a friend" is wrong in general, but may be morally…
I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation
Chandra Bhagavatula, Jena D. Hwang, Doug Downey +7
Commonsense capabilities of pre-trained language models dramatically improve with scale, leading many to believe that scale is the only winning recipe. But is it? Here, we investig…
ComFact: A Benchmark for Linking Contextual Commonsense Knowledge
Silin Gao, Jena D. Hwang, Saya Kanno +3
Understanding rich narratives, such as dialogues and stories, often requires natural language processing systems to access relevant knowledge from commonsense knowledge graphs. How…
Do Androids Laugh at Electric Sheep? Humor "Understanding" Benchmarks from The New Yorker Caption Contest
Jack Hessel, Ana Marasović, Jena D. Hwang +5
Large neural networks can now generate jokes, but do they really "understand" humor? We challenge AI models with three tasks derived from the New Yorker Cartoon Caption Contest: ma…
Penguins Don't Fly: Reasoning about Generics through Instantiations and Exceptions
Emily Allaway, Jena D. Hwang, Chandra Bhagavatula +3
Generics express generalizations about the world (e.g., birds can fly) that are not universally true (e.g., newborn birds and penguins cannot fly). Commonsense knowledge bases, use…
The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning
Jack Hessel, Jena D. Hwang, Jae Sung Park +5
Humans have remarkable capacity to reason abductively and hypothesize about what lies beyond the literal content of an image. By identifying concrete visual clues scattered through…
Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
Peter West, Chandra Bhagavatula, Jack Hessel +6
The common practice for training commonsense models has gone from-human-to-corpus-to-machine: humans author commonsense knowledge graphs in order to train commonsense models. In th…
On-the-Fly Attention Modulation for Neural Generation
Yue Dong, Chandra Bhagavatula, Ximing Lu +4
Despite considerable advancements with deep neural language models (LMs), neural text generation still suffers from degeneration: the generated text is repetitive, generic, self-co…
Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences
Denis Emelin, Ronan Le Bras, Jena D. Hwang +2
In social settings, much of human behavior is governed by unspoken rules of conduct. For artificial systems to be fully integrated into social environments, adherence to such norms…
Edited Media Understanding Frames: Reasoning About the Intent and Implications of Visual Misinformation
Jeff Da, Maxwell Forbes, Rowan Zellers +4
Multimodal disinformation, from 'deepfakes' to simple edits that deceive, is an important societal problem. Yet at the same time, the vast majority of media edits are harmless -- s…
Social Chemistry 101: Learning to Reason about Social and Moral Norms
Maxwell Forbes, Jena D. Hwang, Vered Shwartz +2
Social norms -- the unspoken commonsense rules about acceptable social behavior -- are crucial in understanding the underlying causes and intents of people's actions in narratives.…
Reflective Decoding: Beyond Unidirectional Generation with Off-the-Shelf Language Models
Peter West, Ximing Lu, Ari Holtzman +3
Publicly available, large pretrained LanguageModels (LMs) generate text with remarkable quality, but only sequentially from left to right. As a result, they are not immediately app…
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs
Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras +4
Recent years have brought about a renewed interest in commonsense representation and reasoning in the field of natural language understanding. The development of new commonsense kn…
Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning
Lianhui Qin, Vered Shwartz, Peter West +5
Abductive and counterfactual reasoning, core abilities of everyday human cognition, require reasoning about what might have happened at time t, while conditioning on multiple conte…