10 citations · 12 across the 10 of their papers we have counts for
5 papers · 1 filter
From Rollouts to Recipes: Self-Contained Post-Training for LLMs
Yifei Li, Lingling Zhang, Muye Huang +3
Post-training large language models usually applies a single training recipe to all samples, even though the model's own rollouts reveal different sample-level learning states. We…
Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale
Ang Li, Ben Liu, Bin Han +215
Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve,…
Locomo-Plus: Beyond-Factual Cognitive Memory Evaluation Framework for LLM Agents
Yifei Li, Weidong Guo, Lingling Zhang +6
Long-term conversational memory is a core capability for LLM-based dialogue systems, yet existing benchmarks and evaluation protocols primarily focus on surface-level factual recal…
From Detection to Diagnosis: Advancing Hallucination Analysis with Automated Data Synthesis
Yanyi Liu, Qingwen Yang, Tiezheng Guo +3
Hallucinations in Large Language Models (LLMs), defined as the generation of content inconsistent with facts or context, represent a core obstacle to their reliable deployment in c…
Scaffolded Language Models with Language Supervision for Mixed-Autonomy: A Survey
Matthieu Lin, Jenny Sheng, Andrew Zhao +7
This survey organizes the intricate literature on the design and optimization of emerging structures around post-trained LMs. We refer to this overarching structure as scaffolded L…