From the 1 of 15 linked papers with an AI index.
15 papers
Agentic Routing: The Harness-Native Data Flywheel
Xinchen Liu, Hang Zhou, Yingjie Zong +12
The paper introduces a step‑level routing framework for large language model agents that selects the most suitable model(s) based on the full execution harness state, using logged…
Claw-SWE-Bench: A Benchmark for Evaluating OpenClaw-style Agent Harnesses on Coding Tasks
Mengyu Zheng, Kai Han, Boxun Li +13
General-purpose agents such as OpenClaw are increasingly used as autonomous tool users, but their coding ability is difficult to measure under SWE-bench: a generic agent does not b…
MemoryFormer: Minimize Transformer Computation by Removing Fully-Connected Layers
Ning Ding, Yehui Tang, Haochen Qin +6
In order to reduce the computational complexity of large language models, great efforts have been made to to improve the efficiency of transformer models such as linear attention a…
EAQuant: Enhancing Post-Training Quantization for MoE Models via Expert-Aware Optimization
Zhongqian Fu, Tianyi Zhao, Ning Ding +4
Mixture-of-Experts (MoE) models enable scalable computation and performance in large-scale deep learning but face quantization challenges due to sparse expert activation and dynami…
PocketLLM: Ultimate Compression of Large Language Models via Meta Networks
Ye Tian, Chengcheng Wang, Jing Han +2
As Large Language Models (LLMs) continue to grow in size, storing and transmitting them on edge devices becomes increasingly challenging. Traditional methods like quantization and…
ScaleNet: Scaling up Pretrained Neural Networks with Incremental Parameters
Zhiwei Hao, Jianyuan Guo, Li Shen +4
Recent advancements in vision transformers (ViTs) have demonstrated that larger models often achieve superior performance. However, training these models remains computationally in…