34 citations · 150 across the 33 of their papers we have counts for
6 papers · 1 filter
Generalized Parallel Scaling with Interdependent Generations
Harry Dong, David Brandfonbrener, Eryk Helenowski +5
Parallel LLM inference scaling involves sampling a set of responses for a single input prompt. However, these parallel responses tend to be generated independently from e…
Reinforcement Learning from User Feedback
Eric Han, Jun Chen, Karthik Abinav Sankararaman +8
As large language models (LLMs) are increasingly deployed in diverse user facing applications, aligning them with real user preferences becomes essential. Existing methods like Rei…
Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization
Zishun Yu, Tengyu Xu, Di Jin +9
Solving mathematics problems has been an intriguing capability of large language models, and many efforts have been made to improve reasoning by extending reasoning length, such as…
Matching Algorithms for Blood Donation
Duncan C McElfresh, Christian Kroer, Sergey Pupyrev +5
Global demand for donated blood far exceeds supply, and unmet need is greatest in low- and middle-income countries; experts suggest that large-scale coordination is necessary to al…
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours
Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman +2
Rideshare platforms, when assigning requests to drivers, tend to maximize profit for the system and/or minimize waiting time for riders. Such platforms can exacerbate biases that d…
Allocation Problems in Ride-Sharing Platforms: Online Matching with Offline Reusable Resources
John P Dickerson, Karthik A Sankararaman, Aravind Srinivasan +1
Bipartite matching markets pair agents on one side of a market with agents, items, or contracts on the opposing side. Prior work addresses online bipartite matching markets, where…