Search Results for author:
Found 10 papers, 9 papers with code
Self-Demos: Eliciting Out-of-Demonstration Generalizability in Large Language Models
The generated demos strategically interpolate between existing demos and the given query, transforming the query from OOD to ID.
LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration
Large language models (LLMs) have demonstrated impressive performance in understanding language and executing complex reasoning tasks.
Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
In this paper, we propose R$^3$: Learning Reasoning through Reverse Curriculum Reinforcement Learning (RL), a novel method that employs only outcome supervision to achieve the benefits of process supervision for large language models.
Identifying the Defective: Detecting Damaged Grains for Cereal Appearance Inspection
Cereal grain plays a crucial role in the human diet as a major source of essential nutrients.
An annotated grain kernel image database for visual quality inspection
We present a machine vision-based database named GrainSet for the purpose of visual quality inspection of grain kernels.
The Rise and Potential of Large Language Model Based Agents: A Survey
Many efforts have been made to develop intelligent agents, but they mainly focus on advancement in algorithms or training strategies to enhance specific capabilities or performance on particular tasks.
Causal Kripke Models
This work extends Halpern and Pearl's causal models for actual causality to a possible world semantics environment.
Voices of Her: Analyzing Gender Differences in the AI Publication World
While several previous studies have analyzed gender bias in research, we are still missing a comprehensive analysis of gender differences in the AI community, covering diverse topics and different development trends.
GrainSpace: A Large-scale Dataset for Fine-grained and Domain-adaptive Recognition of Cereal Grains
To the best of our knowledge, GrainSpace is the first publicly released dataset for cereal grain inspection.
Logical Fallacy Detection
In this paper, we propose the task of logical fallacy detection, and provide a new dataset (Logic) of logical fallacies generally found in text, together with an additional challenge set for detecting logical fallacies in climate change claims (LogicClimate).
