3 citations · 8 across the 25 of their papers we have counts for
8 papers · 1 filter
A Tale of LLMs and Induced Small Proxies: Scalable Small Language Models for Knowledge Mining
Sipeng Zhang, Longfei Yun, Zilong Wang +2
At the core of Deep Research is knowledge mining, the task of extracting structured information from massive unstructured text in response to user instructions. Large language mode…
The Price of Format: Diversity Collapse in LLMs
Longfei Yun, Chenyang An, Zilong Wang +2
Instruction-tuned large language models (LLMs) employ structured templates, such as role markers and special tokens, to enforce format consistency during inference. However, we ide…
Bidirectional LMs are Better Knowledge Memorizers? A Benchmark for Real-world Knowledge Injection
Yuwei Zhang, Wenhao Yu, Shangbin Feng +5
Despite significant advances in large language models (LLMs), their knowledge memorization capabilities remain underexplored, due to the lack of standardized and high-quality test…
Codifying Character Logic in Role-Playing
Letian Peng, Jingbo Shang
This paper introduces Codified Profiles for role-playing, a novel approach that represents character logic as structured, executable functions for behavioral decision-making. Each…
Memorize or Generalize? Evaluating LLM Code Generation with Code Rewriting
Lizhe Zhang, Wentao Chen, Li Zhong +3
Large language models (LLMs) have recently demonstrated exceptional code generation capabilities. However, there is a growing debate whether LLMs are mostly doing memorization (i.e…
UltraGen: Extremely Fine-grained Controllable Generation via Attribute Reconstruction and Global Preference Optimization
Longfei Yun, Letian Peng, Jingbo Shang
Fine granularity is an essential requirement for controllable text generation, which has seen rapid growth with the ability of LLMs. However, existing methods focus mainly on a sma…
Cuckoo: An IE Free Rider Hatched by Massive Nutrition in LLM's Nest
Letian Peng, Zilong Wang, Feng Yao +1
Massive high-quality data, both pre-training raw texts and post-training annotations, have been carefully prepared to incubate advanced large language models (LLMs). In contrast, f…
Linear Correlation in LM's Compositional Generalization and Hallucination
Letian Peng, Chenyang An, Shibo Hao +2
The generalization of language models (LMs) is undergoing active debates, contrasting their potential for general intelligence with their struggles with basic knowledge composition…