Search Results for author: Ashwin Paranjape

Found 11 papers, 5 papers with code

Effective Social Chatbot Strategies for Increasing User Initiative

no code implementations SIGDIAL (ACL) 2021 Amelia Hardy, Ashwin Paranjape, Christopher Manning

Many existing chatbots do not effectively support mixed initiative, forcing their users to either respond passively or lead constantly.

Chatbot

Lost in the Middle: How Language Models Use Long Contexts

3 code implementations6 Jul 2023 Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, Percy Liang

While recent language models have the ability to take long contexts as input, relatively little is known about how well they use longer context.

Language Modelling Position +2

Evaluating Human-Language Model Interaction

1 code implementation19 Dec 2022 Mina Lee, Megha Srivastava, Amelia Hardy, John Thickstun, Esin Durmus, Ashwin Paranjape, Ines Gerard-Ursin, Xiang Lisa Li, Faisal Ladhak, Frieda Rong, Rose E. Wang, Minae Kwon, Joon Sung Park, Hancheng Cao, Tony Lee, Rishi Bommasani, Michael Bernstein, Percy Liang

To evaluate human-LM interaction, we develop a new framework, Human-AI Language-based Interaction Evaluation (HALIE), that defines the components of interactive systems and dimensions to consider when designing evaluation metrics.

Language Modelling Question Answering

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

1 code implementation SIGDIAL (ACL) 2022 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 stilted conversational flow.

Language Modelling Spoken Dialogue Systems

You Only Need One Model for Open-domain Question Answering

no code implementations14 Dec 2021 Haejun Lee, Akhil Kedia, Jongwon Lee, Ashwin Paranjape, Christopher D. Manning, Kyoung-Gu Woo

Recent approaches to Open-domain Question Answering refer to an external knowledge base using a retriever model, optionally rerank passages with a separate reranker model and generate an answer using another reader model.

Hard Attention Natural Questions +2

Hindsight: Posterior-guided training of retrievers for improved open-ended generation

no code implementations ICLR 2022 Ashwin Paranjape, Omar Khattab, Christopher Potts, Matei Zaharia, Christopher D. Manning

Many text generation systems benefit from using a retriever to retrieve passages from a textual knowledge corpus (e. g., Wikipedia) which are then provided as additional context to the generator.

Text Generation

Human-like informative conversations: Better acknowledgements using conditional mutual information

1 code implementation NAACL 2021 Ashwin Paranjape, Christopher D. Manning

This is because models trained with two contexts - new factual content and conversational history - generate responses that are non-specific w. r. t.

Specificity

Neural Generation Meets Real People: Towards Emotionally Engaging Mixed-Initiative Conversations

no code implementations27 Aug 2020 Ashwin Paranjape, Abigail See, Kathleen Kenealy, Haojun Li, Amelia Hardy, Peng Qi, Kaushik Ram Sadagopan, Nguyet Minh Phu, Dilara Soylu, Christopher D. Manning

At the end of the competition, Chirpy Cardinal progressed to the finals with an average rating of 3. 6/5. 0, a median conversation duration of 2 minutes 16 seconds, and a 90th percentile duration of over 12 minutes.

World Knowledge

Importance sampling for unbiased on-demand evaluation of knowledge base population

no code implementations EMNLP 2017 Arun Chaganty, Ashwin Paranjape, Percy Liang, Christopher D. Manning

Our first contribution is a new importance-sampling based evaluation which corrects for this bias by annotating a new system{'}s predictions on-demand via crowdsourcing.

Information Retrieval Knowledge Base Population +1

Motifs in Temporal Networks

no code implementations29 Dec 2016 Ashwin Paranjape, Austin R. Benson, Jure Leskovec

Networks are a fundamental tool for modeling complex systems in a variety of domains including social and communication networks as well as biology and neuroscience.

Cannot find the paper you are looking for? You can Submit a new open access paper.