7 citations · 7 across the 9 of their papers we have counts for
9 papers
Bridging the Information Gap: Semantic Densification and Hindsight Distillation for Cold-Start Prediction
Hao Duong Le, Yifei Gao, Huan Li +4
New-user cold-start is a critical bottleneck for e-commerce platforms: predicting user lifetime value (LTV) and conversion rate (CVR) for users with sparse interaction history. Two…
Near-Oracle KV Selection via Pre-hoc Sparsity for Long-Context Inference
Yifei Gao, Lei Wang, Rong-Cheng Tu +3
A core bottleneck in large language model (LLM) inference is the cost of attending over the ever-growing key-value (KV) cache. Although near-oracle top-k KV selection can preserve…
Evaluating Trust in AI, Human, and Co-produced Feedback Among Undergraduate Students
Audrey Zhang, Yifei Gao, Wannapon Suraworachet +2
As generative AI models, particularly large language models (LLMs), transform educational feedback practices in higher education (HE) contexts, understanding students' perceptions…
Beyond Existance: Fulfill 3D Reconstructed Scenes with Pseudo Details
Yifei Gao, Jun Huang, Lei Wang +2
The emergence of 3D Gaussian Splatting (3D-GS) has significantly advanced 3D reconstruction by providing high fidelity and fast training speeds across various scenarios. While rece…
TokenButler: Token Importance is Predictable
Yash Akhauri, Ahmed F AbouElhamayed, Yifei Gao +4
Large Language Models (LLMs) rely on the Key-Value (KV) Cache to store token history, enabling efficient decoding of tokens. As the KV-Cache grows, it becomes a major memory and co…
Compensate Quantization Errors+: Quantized Models Are Inquisitive Learners
Yifei Gao, Jie Ou, Lei Wang +2
The quantization of large language models (LLMs) has been a prominent research area aimed at enabling their lightweight deployment in practice. Existing research about LLM's quanti…
Compensate Quantization Errors: Make Weights Hierarchical to Compensate Each Other
Yifei Gao, Jie Ou, Lei Wang +4
Emergent Large Language Models (LLMs) use their extraordinary performance and powerful deduction capacity to discern from traditional language models. However, the expenses of comp…
Bootstrap-GS: Self-Supervised Augmentation for High-Fidelity Gaussian Splatting
Yifei Gao, Kerui Ren, Jie Ou +3
Recent advancements in 3D Gaussian Splatting (3D-GS) have established new benchmarks for rendering quality and efficiency in 3D reconstruction. However, 3D-GS faces critical limita…
Pay Attention to What You Need
Yifei Gao, Shaohong Chen, Lei Wang +5
Although large language models (LLMs) have achieved significant success in natural language processing, they still struggle with long-context comprehension. Traditional approaches…