collaborators

7 papers

cs.AI2026

SonicSampler: Unified Tile-Aware Kernels for LLM Sampling and Speculative Verification

Pragaash Ponnusamy, Shivam Sahni, Jue Wang +1

Sampling in LLM inference comprises a combinatorial set of logit processing, token selection, and verification operations for speculative decoding. However, existing implementation…

cs.LG2026

Search Your Block Floating Point Scales!

Tanmaey Gupta, Hayden Prairie, Xiaoxia Wu +10

Quantization has emerged as a standard technique for accelerating inference for generative models by enabling faster low-precision computations and reduced memory transfers. Recent…

cs.LG2026

SAW-INT4: System-Aware 4-Bit KV-Cache Quantization for Real-World LLM Serving

Jinda Jia, Jisen Li, Zhongzhu Zhou +8

KV-cache memory is a major bottleneck in real-world LLM serving, where systems must simultaneously support latency-sensitive small-batch requests and high-throughput concurrent wor…

cs.AI2026

Squeeze Evolve: Unified Multi-Model Orchestration for Verifier-Free Evolution

Monishwaran Maheswaran, Leon Lakhani, Zhongzhu Zhou +16

We show that verifier-free evolution is bottlenecked by both diversity and efficiency: without external correction, repeated evolution accelerates collapse toward narrow modes, whi…

cs.CL2026

Understanding and Steering the Cognitive Behaviors of Reasoning Models at Test-Time

Zhenyu Zhang, Xiaoxia Wu, Zhongzhu Zhou +7

Large Language Models (LLMs) often rely on long chain-of-thought (CoT) reasoning to solve complex tasks. While effective, these trajectories are frequently inefficient, leading to…

cs.AI2025

Staircase Streaming for Low-Latency Multi-Agent Inference

Junlin Wang, Jue Wang, Zhen +5

Recent advances in large language models (LLMs) opened up new directions for leveraging the collective expertise of multiple LLMs. These methods, such as Mixture-of-Agents, typical…