activity
20232026
most citedOnline Speculative Decoding

3 citations · 5 across the 8 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.LG2026

EasyPPO: Stabilizing the Critic Is Key

Xuanyi Zhou, Qiuyang Mang, Huanzhi Mao +7

A key strength of Proximal Policy Optimization (PPO) is its learned critic, which uses historical trajectories collected during reinforcement learning to estimate expected returns…

cs.CL2026

When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis

Kaiyuan Liu, Qiuyang Mang, Bo Peng +6

Large language model (LLM) agents allocate test-time compute adaptively as they revise solutions, use tools, explore alternatives, and decide when to stop. This test-time strategy…

cs.AI2026

Combee: Scaling Prompt Learning for Self-Improving Language Model Agents

Hanchen Li, Runyuan He, Qizheng Zhang +11

Recent advances in prompt learning allow large language model agents to acquire task-relevant knowledge from inference-time context without parameter changes. For example, existing…

cs.CV2026

SVG-EAR: Parameter-Free Linear Compensation for Sparse Video Generation via Error-aware Routing

Xuanyi Zhou, Qiuyang Mang, Shuo Yang +7

Diffusion Transformers (DiTs) have become a leading backbone for video generation, yet their quadratic attention cost remains a major bottleneck. Sparse attention reduces this cost…

cs.AI2026

Qrita: High-performance Top-k and Top-p using Pivot-based Truncation and Selection

Jongseok Park, Sunga Kim, Alvin Cheung +1

Despite their importance in model sampling, efficient implementation of Top-k and Top-p algorithms for large vocabularies remains a significant challenge. Existing approaches often…

cs.CL2026

Speculative Decoding: Performance or Illusion?

Xiaoxuan Liu, Jiaxiang Yu, Jongseok Park +2

Speculative decoding (SD) has become a popular technique to accelerate Large Language Model (LLM) inference, yet its real-world effectiveness remains unclear as prior evaluations r…