1 citations · 1 across the 9 of their papers we have counts for
5 papers · 1 filter
Answer First, Reason Later: Aligning Search Relevance via Mode-Balanced Reinforcement Learning
Shijie Zhang, Xiang Guo, Rujun Guo +4
Building a search relevance model that achieves both low latency and high performance is a long-standing challenge in the search industry. To satisfy the millisecond-level response…
ETR: Outcome-Guided Elastic Trust Regions for Policy Optimization
Shijie Zhang, Kevin Zhang, Zheyuan Gu +5
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an important paradigm for unlocking reasoning capabilities in large language models, exemplified by the success…
Meta-probabilistic Modeling
Kevin Zhang, Yixin Wang
Probabilistic graphical models (PGMs) are widely used to discover latent structure in data, but their success hinges on selecting an appropriate model design. In practice, model sp…
Aligning AI-driven discovery with human intuition
Kevin Zhang, Judah Goldfeder, Hod Lipson
As data-driven modeling of physical dynamical systems becomes more prevalent, a new challenge is emerging: making these models more compatible and aligned with existing human knowl…
Deep Autoregressive Models as Causal Inference Engines
Daniel Jiwoong Im, Kevin Zhang, Nakul Verma +1
Existing causal inference (CI) models are often restricted to data with low-dimensional confounders and singleton actions. We propose an autoregressive (AR) CI framework capable of…