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Found 14 papers, 5 papers with code
Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models
This survey seeks to fill this gap by offering a unified perspective on Long CoT.
Text2World: Benchmarking Large Language Models for Symbolic World Model Generation
Recently, there has been growing interest in leveraging large language models (LLMs) to generate symbolic world models from textual descriptions.
Cross-Lingual Text-Rich Visual Comprehension: An Information Theory Perspective
To mitigate this issue, we propose MVCL-MI (Maximization of Vision-Language Cross-Lingual Mutual Information), where a visual-text cross-lingual alignment is built by maximizing mutual information between the model's outputs and visual information.
EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents
Heterogeneous multi-robot systems (HMRS) have emerged as a powerful approach for tackling complex tasks that single robots cannot manage alone.
HiAgent: Hierarchical Working Memory Management for Solving Long-Horizon Agent Tasks with Large Language Model
Specifically, HiAgent prompts LLMs to formulate subgoals before generating executable actions and enables LLMs to decide proactively to replace previous subgoals with summarized observations, retaining only the action-observation pairs relevant to the current subgoal.
AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation
Moreover, to increase the difficulty diversity of generated planning tasks, we propose a bidirectional evolution method, Bi-Evol, that evolves planning tasks from easier and harder directions to synthesize a task set with a smoother difficulty curve.
DAG-Plan: Generating Directed Acyclic Dependency Graphs for Dual-Arm Cooperative Planning
Extensive experiments demonstrate the superiority of DAG-Plan over directly using LLM to generate linear task sequence, achieving 52. 8% higher efficiency compared to the single-arm task planning and 48% higher success rate of the dual-arm task planning.
Needle In A Multimodal Haystack
In this work, we present Needle In A Multimodal Haystack (MM-NIAH), the first benchmark specifically designed to systematically evaluate the capability of existing MLLMs to comprehend long multimodal documents.
AnalogCoder: Analog Circuit Design via Training-Free Code Generation
Analog circuit design is a significant task in modern chip technology, focusing on the selection of component types, connectivity, and parameters to ensure proper circuit functionality.
KET-QA: A Dataset for Knowledge Enhanced Table Question Answering
In this paper, we propose to use a knowledge base (KB) as the external knowledge source for TableQA and construct a dataset KET-QA with fine-grained gold evidence annotation.
RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis
Robotic behavior synthesis, the problem of understanding multimodal inputs and generating precise physical control for robots, is an important part of Embodied AI.
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Visual Question Answering
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Tree-Planner: Efficient Close-loop Task Planning with Large Language Models
This paper studies close-loop task planning, which refers to the process of generating a sequence of skills (a plan) to accomplish a specific goal while adapting the plan based on real-time observations.
EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought
In this work, we introduce EmbodiedGPT, an end-to-end multi-modal foundation model for embodied AI, empowering embodied agents with multi-modal understanding and execution capabilities.
TaCube: Pre-computing Data Cubes for Answering Numerical-Reasoning Questions over Tabular Data
Existing auto-regressive pre-trained language models (PLMs) like T5 and BART, have been well applied to table question answering by UNIFIEDSKG and TAPEX, respectively, and demonstrated state-of-the-art results on multiple benchmarks.
