2 citations · 8 across the 11 of their papers we have counts for
11 papers
Contextual Procurement Auctions with Bandit Learning
Yiling Chen, Shi Feng, Sadie Zhao
We study repeated procurement auctions in which producers have private costs and the platform must learn the context-dependent value of selecting each producer. We evaluate perform…
Peer-Predictive Self-Training for Language Model Reasoning
Shi Feng, Hanlin Zhang, Fan Nie +2
Mechanisms for continued self-improvement of language models without external supervision remain an open challenge. We propose Peer-Predictive Self-Training (PST), a label-free fin…
Data Reliability Scoring
Yiling Chen, Shi Feng, Paul Kattuman +1
How can we assess the reliability of a dataset without access to ground truth? We introduce the problem of reliability scoring for datasets collected from potentially strategic sou…
Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective
Siwei Wang, Yifei Shen, Haoran Sun +5
Recent reinforcement learning (RL) methods have substantially enhanced the planning capabilities of Large Language Models (LLMs), yet the theoretical basis for their effectiveness…
Carrot and Stick: Eliciting Comparison Data and Beyond
Yiling Chen, Shi Feng, Fang-Yi Yu
Comparison data elicited from people are fundamental to many machine learning tasks, including reinforcement learning from human feedback for large language models and estimating r…
ALPINE: Unveiling the Planning Capability of Autoregressive Learning in Language Models
Siwei Wang, Yifei Shen, Shi Feng +3
Planning is a crucial element of both human intelligence and contemporary large language models (LLMs). In this paper, we initiate a theoretical investigation into the emergence of…
A Correction of Pseudo Log-Likelihood Method
Shi Feng, Nuoya Xiong, Zhijie Zhang +1
Pseudo log-likelihood is a type of maximum likelihood estimation (MLE) method used in various fields including contextual bandits, influence maximization of social networks, and ca…
Combinatorial Causal Bandits without Graph Skeleton
Shi Feng, Nuoya Xiong, Wei Chen
In combinatorial causal bandits (CCB), the learning agent chooses a subset of variables in each round to intervene and collects feedback from the observed variables to minimize exp…
Peer Prediction for Learning Agents
Shi Feng, Fang-Yi Yu, Yiling Chen
Peer prediction refers to a collection of mechanisms for eliciting information from human agents when direct verification of the obtained information is unavailable. They are desig…
Combinatorial Causal Bandits
Shi Feng, Wei Chen
In combinatorial causal bandits (CCB), the learning agent chooses at most variables in each round to intervene, collects feedback from the observed variables, with the goal of…
Causal Inference for Influence Propagation -- Identifiability of the Independent Cascade Model
Shi Feng, Wei Chen
Independent cascade (IC) model is a widely used influence propagation model for social networks. In this paper, we incorporate the concept and techniques from causal inference to s…