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Found 11 papers, 10 papers with code
Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning
To alleviate the long-existing difficulties brought by sparse rewards in RL, which are even exacerbated by the partial correctness of the long chain of thought for reasoning tasks, we further apply a token-level reward model to sample important tokens in reasoning trajectories for learning.
Are Your LLMs Capable of Stable Reasoning?
The rapid advancement of Large Language Models (LLMs) has demonstrated remarkable progress in complex reasoning tasks.
MindSearch: Mimicking Human Minds Elicits Deep AI Searcher
Inspired by the cognitive process when humans solve these problems, we introduce MindSearch to mimic the human minds in web information seeking and integration, which can be instantiated by a simple yet effective LLM-based multi-agent framework.
2D Semantic Segmentation task 1 (8 classes)
graph construction
+1
CIBench: Evaluating Your LLMs with a Code Interpreter Plugin
Our evaluation framework includes an evaluation dataset and two evaluation modes.
AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source Data
Open-source Large Language Models (LLMs) and their specialized variants, particularly Code LLMs, have recently delivered impressive performance.
InternLM2 Technical Report
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI).
Ranked #5 on
Long-Context Understanding
on Ada-LEval (BestAnswer)
Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models
Open-sourced Large Language Models (LLMs) have achieved great success in various NLP tasks, however, they are still far inferior to API-based models when acting as agents.
InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning
We further explore how to use LEAN to solve math problems and study its performance under the setting of multi-task learning which shows the possibility of using LEAN as a unified platform for solving and proving in math.
T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step
Based on that, we further introduce T-Eval to evaluate the tool utilization capability step by step.
MultiModal-GPT: A Vision and Language Model for Dialogue with Humans
To further enhance the ability to chat with humans of the MultiModal-GPT, we utilize language-only instruction-following data to train the MultiModal-GPT jointly.
supervised adptive threshold network for instance segmentation
Currently, instance segmentation is attracting more and more attention in machine learning region.
