6 papers
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…
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:…
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…
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-…
KV-CoRE: Benchmarking Data-Dependent Low-Rank Compressibility of KV-Caches in LLMs
Jian Chen, Zhuoran Wang, Jiayu Qin +6
Large language models rely on kv-caches to avoid redundant computation during autoregressive decoding, but as context length grows, reading and writing the cache can quickly satura…
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…