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Found 7 papers, 3 papers with code
LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
(2) We develop LLM Reasoners, a library for standardized modular implementation of existing and new reasoning algorithms, under a unified formulation of the search, reward, and world model components.
No more optimization rules: LLM-enabled policy-based multi-modal query optimizer
As a critical (or could even be the most important) step that significantly impacts the execution performance of the query plan, such analysis and attempts should not be missed.
Can Knowledge Graphs Simplify Text?
Knowledge Graph (KG)-to-Text Generation has seen recent improvements in generating fluent and informative sentences which describe a given KG.
Simple Rule Injection for ComplEx Embeddings
Recent works in neural knowledge graph inference attempt to combine logic rules with knowledge graph embeddings to benefit from prior knowledge.
Reasoning with Language Model is Planning with World Model
RAP on LLAMA-33B surpasses CoT on GPT-4 with 33% relative improvement in a plan generation setting.
A Survey On Few-shot Knowledge Graph Completion with Structural and Commonsense Knowledge
In this paper, we comprehensively survey previous attempts on such tasks in the form of a series of methods and applications.
LIDER: An Efficient High-dimensional Learned Index for Large-scale Dense Passage Retrieval
As the basic unit of LIDER to index and search data, a core model includes an adapted recursive model index (RMI) and a dimension reduction component which consists of an extended SortingKeys-LSH (SK-LSH) and a key re-scaling module.
