most citedFrom Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs

1 citations · 1 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CL2026

Kimi K3: Open Frontier Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +398

We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…

stat.ME20261 cited

From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs

Yichi Zhang, Ignacio Martinez

Large Language Models (LLMs) are increasingly used to automate classification tasks in business, such as analyzing customer satisfaction from text. However, the inherent stochastic…

cs.IR2026

RLPO: Residual Listwise Preference Optimization for Long-Context Review Ranking

Hao Jiang, Zhi Yang, Annan Wang +2

Review ranking is pivotal in e-commerce for prioritizing diagnostic and authentic feedback from the deluge of user-generated content. While large language models have improved sema…

cs.CL2026

Kimi K2.5: Visual Agentic Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +339

We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…

cs.AI2026

Small-Margin Preferences Still Matter-If You Train Them Right

Jinlong Pang, Zhaowei Zhu, Na Di +4

Preference optimization methods such as DPO align large language models (LLMs) using paired comparisons, but their effectiveness can be highly sensitive to the quality and difficul…

stat.ML2025

Fisher Random Walk: Automatic Debiasing Contextual Preference Inference for Large Language Model Evaluation

Yichi Zhang, Alexander Belloni, Ethan X. Fang +2

Motivated by the need for rigorous and scalable evaluation of large language models, we study contextual preference inference for pairwise comparison functionals of context-depende…