Search Results for author:
Found 8 papers, 5 papers with code
Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization
Large Language Models exhibit robust problem-solving capabilities for diverse tasks.
Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives
Experiments conducted on a series of reasoning and translation tasks with different LLMs serve to underscore the effectiveness and generality of our strategy.
TaskBench: Benchmarking Large Language Models for Task Automation
To this end, we introduce TaskBench to evaluate the capability of LLMs in task automation.
An Expression Tree Decoding Strategy for Mathematical Equation Generation
To generate a tree with expression as its node, we employ a layer-wise parallel decoding strategy: we decode multiple independent expressions (leaf nodes) in parallel at each layer and repeat parallel decoding layer by layer to sequentially generate these parent node expressions that depend on others.
Ranked #2 on
Math Word Problem Solving
on MathQA
Data-Copilot: Bridging Billions of Data and Humans with Autonomous Workflow
Various industries such as finance, meteorology, and energy generate vast amounts of heterogeneous data every day.
PromptNER: Prompt Locating and Typing for Named Entity Recognition
Prompt learning is a new paradigm for utilizing pre-trained language models and has achieved great success in many tasks.
Ranked #1 on
Nested Named Entity Recognition
on ACE 2004
Query-based Instance Discrimination Network for Relational Triple Extraction
Joint entity and relation extraction has been a core task in the field of information extraction.
Contrastive Learning
Joint Entity and Relation Extraction
+1
Multi-View Reasoning: Consistent Contrastive Learning for Math Word Problem
Math word problem solver requires both precise relation reasoning about quantities in the text and reliable generation for the diverse equation.
Ranked #1 on
Math Word Problem Solving
on Math23K
(using extra training data)
