activity
20232026
most citedData Market Design through Deep Learning

4 citations · 5 across the 11 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.AI2026

Cogentic: Multi-Agent Orchestration for Automated Proof Discovery

Yang Cai, Vineet Gupta, Yanchen Jiang +4

We present Cogentic, a multi-agent harness for automated proof discovery on open research problems. While frontier language models can generate strong mathematical ideas in a singl…

cs.GT2026

Efficiency of Generalized Proportional First-Price Auctions Under Auto-bidding

Yang Cai, Vineet Gupta, Yanchen Jiang +4

Auto-bidding is now widely adopted in online advertising platforms, allowing advertisers to specify high-level campaign objectives--such as maximizing total value subject to a retu…

cs.IR2026

One Model, Two Markets: Bid-Aware Generative Recommendation

Yanchen Jiang, Zhe Feng, Christopher P. Mah +2

Generative Recommender Systems using semantic ids, such as TIGER (Rajput et al., 2023), have emerged as a widely adopted competitive paradigm in sequential recommendation. However,…

cs.SI2026★ 1 cited

The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement

Jonathan Stray, Ian Baker, George Beknazar-Yuzbashev +41

We report the first direct comparisons of multiple alternative social media algorithms on multiple platforms on outcomes of societal interest. We used a browser extension to modify…

cs.AI2026

LLM Active Alignment: A Nash Equilibrium Perspective

Tonghan Wang, Yuqi Pan, Xinyi Yang +3

We develop a game-theoretic framework for predicting and steering the behavior of populations of large language models (LLMs) through Nash equilibrium (NE) analysis. To avoid the i…