2 citations · 5 across the 11 of their papers we have counts for
4 papers · 1 filter
Value Gradient Guidance for Flow Matching Alignment
Zhen Liu, Tim Z. Xiao, Carles Domingo-Enrich +2
While methods exist for aligning flow matching models--a popular and effective class of generative models--with human preferences, existing approaches fail to achieve both adaptati…
Flipping Against All Odds: Reducing LLM Coin Flip Bias via Verbalized Rejection Sampling
Tim Z. Xiao, Johannes Zenn, Zhen Liu +3
Large language models (LLMs) can often accurately describe probability distributions using natural language, yet they still struggle to generate faithful samples from them. This mi…
Reparameterized LLM Training via Orthogonal Equivalence Transformation
Zeju Qiu, Simon Buchholz, Tim Z. Xiao +3
While large language models (LLMs) are driving the rapid advancement of artificial intelligence, effectively and reliably training these large models remains one of the field's mos…
Generating Symbolic World Models via Test-time Scaling of Large Language Models
Zhouliang Yu, Yuhuan Yuan, Tim Z. Xiao +5
Solving complex planning problems requires Large Language Models (LLMs) to explicitly model the state transition to avoid rule violations, comply with constraints, and ensure optim…