Search Results for author:
Found 11 papers, 5 papers with code
Say More with Less: Understanding Prompt Learning Behaviors through Gist Compression
It finetunes the compression plugin module and uses the representations of gist tokens to emulate the raw prompts in the vanilla language model.
Cleaner Pretraining Corpus Curation with Neural Web Scraping
The web contains large-scale, diverse, and abundant information to satisfy the information-seeking needs of humans.
ActiveRAG: Revealing the Treasures of Knowledge via Active Learning
Retrieval Augmented Generation (RAG) has introduced a new paradigm for Large Language Models (LLMs), aiding in the resolution of knowledge-intensive tasks.
MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization
Scientific data visualization plays a crucial role in research by enabling the direct display of complex information and assisting researchers in identifying implicit patterns.
UltraLink: An Open-Source Knowledge-Enhanced Multilingual Supervised Fine-tuning Dataset
Different from previous works that simply translate English instructions, we consider both the language-specific and language-agnostic abilities of LLMs.
UniMem: Towards a Unified View of Long-Context Large Language Models
Although there exist various methods devoted to enhancing the long-context processing ability of large language models (LLMs), they are developed in an isolated manner and lack systematic analysis and integration of their strengths, hindering further developments.
GitAgent: Facilitating Autonomous Agent with GitHub by Tool Extension
As GitHub has hosted a multitude of repositories which can be seen as a good resource for tools, a promising solution is that LLM-based agents can autonomously integrate the repositories in GitHub according to the user queries to extend their tool set.
Local Hypergraph-based Nested Named Entity Recognition as Query-based Sequence Labeling
There has been a growing academic interest in the recognition of nested named entities in many domains.
Event Identification as a Decision Process with Non-linear Representation of Text
We propose scale-free Identifier Network(sfIN), a novel model for event identification in documents.
Object-oriented Neural Programming (OONP) for Document Understanding
We propose Object-oriented Neural Programming (OONP), a framework for semantically parsing documents in specific domains.
