activity
20182026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 646 across the 8 of their papers we have counts for

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Showing cs.CLShow all

5 papers · 1 filter

cs.CL2024★ 3 cited

Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance

Kaitlyn Zhou, Jena D. Hwang, Xiang Ren +3

The ability to communicate uncertainty, risk, and limitation is crucial for the safety of large language models. However, current evaluations of these abilities rely on simple cali…

cs.CL2023★ 5 cited

Topical-Chat: Towards Knowledge-Grounded Open-Domain Conversations

Karthik Gopalakrishnan, Behnam Hedayatnia, Qinlang Chen +5

Building socialbots that can have deep, engaging open-domain conversations with humans is one of the grand challenges of artificial intelligence (AI). To this end, bots need to be…

cs.CL2022★ 10 cited

Alexa, Let's Work Together: Introducing the First Alexa Prize TaskBot Challenge on Conversational Task Assistance

Anna Gottardi, Osman Ipek, Giuseppe Castellucci +27

Since its inception in 2016, the Alexa Prize program has enabled hundreds of university students to explore and compete to develop conversational agents through the SocialBot Grand…

cs.CL2022★ 565 cited

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…

cs.CL2018★ 61 cited

Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize

Chandra Khatri, Behnam Hedayatnia, Anu Venkatesh +19

Building open domain conversational systems that allow users to have engaging conversations on topics of their choice is a challenging task. Alexa Prize was launched in 2016 to tac…