1 citations · 1 across the 7 of their papers we have counts for
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RFG: Self-Improving Diffusion Large Language Models with Reward-Free Guidance
Tianlang Chen, Minkai Xu, Jure Leskovec +1
Diffusion Large Language Models (dLLMs) have shown strong reasoning capabilities, yet further improving them typically requires costly post-training with additional data and superv…
Fractional Reasoning via Latent Steering Vectors Improves Inference Time Compute
Sheng Liu, Tianlang Chen, Pan Lu +4
Test-time compute has emerged as a powerful paradigm for improving the performance of large language models (LLMs), where generating multiple outputs or refining individual chains…
Exchangeability in Neural Network and its Application to Dynamic Pruning
Pu, Yi, Tianlang Chen +2
Modern neural networks (NN) contain an ever-growing number of parameters, substantially increasing the memory and computational cost of inference. Researchers have explored various…
RelGNN: Composite Message Passing for Relational Deep Learning
Tianlang Chen, Charilaos Kanatsoulis, Jure Leskovec
Predictive tasks on relational databases are critical in real-world applications spanning e-commerce, healthcare, and social media. To address these tasks effectively, Relational D…