4 papers · 1 filter
Inference-Cost-Aware Dynamic Tree Construction for Efficient Inference in Large Language Models
Yinrong Hong, Zhiquan Tan, Kai Hu
Large Language Models (LLMs) face significant inference latency challenges stemming from their autoregressive design and large size. To address this, speculative decoding emerges a…
Nex-N1: Agentic Models Trained via a Unified Ecosystem for Large-Scale Environment Construction
AGI Team, Yuxuan Cai, Lu Chen +62
The evolution of Large Language Models (LLMs) from passive responders to autonomous agents necessitates a fundamental shift in learning paradigms -- from static imitation to incent…
MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space
Yicheng Chen, Yining Li, Kai Hu +3
Data quality and diversity are key to the construction of effective instruction-tuning datasets. % With the increasing availability of open-source instruction-tuning datasets, it i…
DocTabQA: Answering Questions from Long Documents Using Tables
Haochen Wang, Kai Hu, Haoyu Dong +1
We study a new problem setting of question answering (QA), referred to as DocTabQA. Within this setting, given a long document, the goal is to respond to questions by organizing th…