activity
20192024
most citedAutomatic Story Generation: Challenges and Attempts

7 citations · 31 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CR2024

PAPILLON: Privacy Preservation from Internet-based and Local Language Model Ensembles

Li Siyan, Vethavikashini Chithrra Raghuram, Omar Khattab +2

Users can divulge sensitive information to proprietary LLM providers, raising significant privacy concerns. While open-source models, hosted locally on the user's machine, alleviat…

cs.CL2024

EDEN: Empathetic Dialogues for English learning

Li Siyan, Teresa Shao, Zhou Yu +1

Dialogue systems have been used as conversation partners in English learning, but few have studied whether these systems improve learning outcomes. Student passion and perseverance…

cs.CL2024★ 3 cited

Using Adaptive Empathetic Responses for Teaching English

Li Siyan, Teresa Shao, Zhou Yu +1

Existing English-teaching chatbots rarely incorporate empathy explicitly in their feedback, but empathetic feedback could help keep students engaged and reduce learner anxiety. Tow…

cs.CL2022★ 1 cited

Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference

Eric Mitchell, Joseph J. Noh, Siyan Li +5

While large pre-trained language models are powerful, their predictions often lack logical consistency across test inputs. For example, a state-of-the-art Macaw question-answering…

cs.CL2022★ 3 cited

Systematicity in GPT-3's Interpretation of Novel English Noun Compounds

Siyan Li, Riley Carlson, Christopher Potts

Levin et al. (2019) show experimentally that the interpretations of novel English noun compounds (e.g., stew skillet), while not fully compositional, are highly predictable based o…

cs.CL2022

When can I Speak? Predicting initiation points for spoken dialogue agents

Siyan Li, Ashwin Paranjape, Christopher D. Manning

Current spoken dialogue systems initiate their turns after a long period of silence (700-1000ms), which leads to little real-time feedback, sluggish responses, and an overall stilt…

cs.CL2021★ 4 cited

Inferring the Reader: Guiding Automated Story Generation with Commonsense Reasoning

Xiangyu Peng, Siyan Li, Sarah Wiegreffe +1

Transformer-based language model approaches to automated story generation currently provide state-of-the-art results. However, they still suffer from plot incoherence when generati…

cs.LG2021

Growing 3D Artefacts and Functional Machines with Neural Cellular Automata

Shyam Sudhakaran, Djordje Grbic, Siyan Li +4

Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells. Re…

cs.CL2021★ 7 cited

Automatic Story Generation: Challenges and Attempts

Amal Alabdulkarim, Siyan Li, Xiangyu Peng

The scope of this survey paper is to explore the challenges in automatic story generation. We hope to contribute in the following ways: 1. Explore how previous research in story ge…

cs.CL2020★ 7 cited

Reducing Non-Normative Text Generation from Language Models

Xiangyu Peng, Siyan Li, Spencer Frazier +1

Large-scale, transformer-based language models such as GPT-2 are pretrained on diverse corpora scraped from the internet. Consequently, they are prone to generating non-normative t…

cs.RO2019★ 6 cited

Adaptable Human Intention and Trajectory Prediction for Human-Robot Collaboration

Abulikemu Abuduweili, Siyan Li, Changliu Liu

To engender safe and efficient human-robot collaboration, it is critical to generate high-fidelity predictions of human behavior. The challenges in making accurate predictions lie…