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20212026
most citedFrom Who You Know to What You Read: Augmenting Scientific Recommendations with Implicit Social Networks

24 citations · 126 across the 11 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.HC2024

Cocoa: Co-Planning and Co-Execution with AI Agents

K. J. Kevin Feng, Kevin Pu, Matt Latzke +6

As AI agents take on increasingly long-running tasks involving sophisticated planning and execution, there is a corresponding need for novel interaction designs that enable deeper…

cs.CL2024★ 6 cited

OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs

Akari Asai, Jacqueline He, Rulin Shao +22

Scientific progress depends on researchers' ability to synthesize the growing body of literature. Can large language models (LMs) assist scientists in this task? We introduce OpenS…

cs.HC2024★ 14 cited

IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedback

Kevin Pu, K. J. Kevin Feng, Tovi Grossman +6

Research ideation involves broad exploring and deep refining ideas. Both require deep engagement with literature. Existing tools focus primarily on idea broad generation, yet offer…

cs.DL2024★ 20 cited

PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers

Yoonjoo Lee, Hyeonsu B. Kang, Matt Latzke +4

With the rapid growth of scholarly archives, researchers subscribe to "paper alert" systems that periodically provide them with recommendations of recently published papers that ar…

cs.HC2024★ 11 cited

Mitigating Barriers to Public Social Interaction with Meronymous Communication

Nouran Soliman, Hyeonsu B Kang, Matthew Latzke +4

In communities with social hierarchies, fear of judgment can discourage communication. While anonymity may alleviate some social pressure, fully anonymous spaces enable toxic behav…