9 citations · 26 across the 18 of their papers we have counts for
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cs.CL2026
Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent
Lei Bai, Zongsheng Cao, Yang Chen +50
We introduce Agents-A1, a 35B Mixture-of-Experts Agentic Model that reaches trillion-parameter-level performance by scaling the agent horizon. We investigate agent-horizon scaling…
cs.CL2026
Chain-based Distillation for Effective Initialization of Variable-Sized Small Language Models
Boyu Shi, YiCheng Jiang, Chang Liu +3
Large language models (LLMs) achieve strong performance but remain costly to deploy in resource-constrained settings. Training small language models (SLMs) from scratch is computat…
cs.CL2026
LSTM-MAS: A Long Short-Term Memory Inspired Multi-Agent System for Long-Context Understanding
Yichen Jiang, Jiakang Yuan, Chongjun Tu +2
Effectively processing long contexts remains a fundamental yet unsolved challenge for large language models (LLMs). Existing single-LLM-based methods primarily reduce the context w…