5 papers
Marginal Advantage Accumulation for Memory-Driven Agent Self-Evolution
Mingyu Yang, Keye Zheng, Congchao Cheng +4
In batch-style trace distillation, the same memory operation may receive contradictory feedback across different batches. Existing methods lack a cross-batch, operation-level evide…
Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling
Parsa Ashrafi Fashi, Utkarsh Saxena, Mehdi Rezagholizadeh +7
Hybrid sequence models that combine efficient Transformer components with linear sequence modeling blocks are a promising alternative to pure Transformers, but most are still pretr…
UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience
Zichuan Lin, Feiyu Liu, Yijun Yang +9
Autonomous mobile GUI agents have attracted increasing attention along with the advancement of Multimodal Large Language Models (MLLMs). However, existing methods still suffer from…
DSDE: Dynamic Speculative Decoding with KLD Stability for Real-World Serving
Mingyu Yang, Jae-Young Choi, Kihyo Moon +2
Speculative decoding accelerates large language model inference, but its reliance on a fixed speculation length is suboptimal in large-batch serving environments with diverse reque…
ELIS: Efficient LLM Iterative Scheduling System with Response Length Predictor
Seungbeom Choi, Jeonghoe Goo, Eunjoo Jeon +2
We propose ELIS, a serving system for Large Language Models (LLMs) featuring an Iterative Shortest Remaining Time First (ISRTF) scheduler designed to efficiently manage inference t…