collaborators

10 papers

cs.AI2026

RelaxKV: Recomputation Guided by the Query with Sparse Context Attention for Efficient KV Cache Reuse

Ruoling Qi, Yirui Liu, Xuaner Wu +5

Cross-request KV caching reduces the prefill cost of Retrieval-Augmented Generation (RAG), but conventional prefix caching severely limits cache reuse across requests. Position-Ind…

cs.AI2026

Just Let Linear States Forget the Distant Past: Prefix Caching via Suffix Replay for Hybrid LLMs

Yirui Liu, Ruoling Qi, Xuaner Wu +6

Hybrid LLMs interleave full-attention layers with linear-attention layers to reduce long-context inference cost, but this structure complicates prefix caching. Full-attention KV ca…

cs.AI2026

REVISE: Validity-Guided Recovery for Online Revisions in Agent Workflows

Ruoling Qi, Xuaner Wu, Penghang Liu +2

Agent revisions expose a fundamental correctness--efficiency trade-off during concurrent execution. Discarding ongoing work preserves latest-version correctness but wastes progress…

cs.LG2026

Tail-Replay: Escaping the Curse of Linear Attention in Prefix Caching for Hybrid LLMs

Yirui Liu, Ruoling Qi, Xuaner Wu +2

Hybrid large language models interleave full-attention layers with linear-attention layers to reduce the cost of long-context inference. This structure complicates prefix caching:…

cs.AI2026

LinearKV: One Cached State Suffices for Position-Independent Caching in Hybrid LLMs

Yirui Liu, Ruoling Qi, Longwen Wang +5

LLM serving is increasingly accelerated by position-independent caching (PIC). Existing PIC methods, however, are built for full-attention models, where a token-indexed KV cache un…

cs.AI2026

PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations

Yang Zhang, Jiangyuan Zhao, Chenyou Fan +11

Vision-Language-Action (VLA) models advance robotic control via strong visual-linguistic priors. However, existing VLAs predominantly frame pretraining as supervised behavior cloni…

cs.CL2026

Swift-SVD: Theoretical Optimality Meets Practical Efficiency in Low-Rank LLM Compression

Ruoling Qi, Yirui Liu, Xuaner Wu +6

The deployment of Large Language Models is constrained by the memory and bandwidth demands of static weights and dynamic Key-Value cache. SVD-based compression provides a hardware-…

cs.CV2026

TeleBoost: A Systematic Alignment Framework for High-Fidelity, Controllable, and Robust Video Generation

Yuanzhi Liang, Xuan'er Wu, Yirui Liu +12

Post-training is the decisive step for converting a pretrained video generator into a production-oriented model that is instruction-following, controllable, and robust over long te…

cs.LG2026

Beyond Binary: Turning Partial Success into Dense Verifiable Rewards for Reinforcement Learning in Code Generation

Longwen Wang, Yirui Liu, Xuan'er Wu +6

Effective reward design is a central challenge in Reinforcement Learning (RL) for code generation. Mainstream test-suite-level outcome rewards enforce functional correctness but in…

cs.CV2025

TeleWorld: Towards Dynamic Multimodal Synthesis with a 4D World Model

Yabo Chen, Yuanzhi Liang, Jiepeng Wang +24

World models aim to endow AI systems with the ability to represent, generate, and interact with dynamic environments in a coherent and temporally consistent manner. While recent vi…