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Found 12 papers, 6 papers with code
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated reasoning, robust perception, and versatile action across diverse domains.
Ranked #1 on
Continual Learning
on AIDS
(using extra training data)
ExScene: Free-View 3D Scene Reconstruction with Gaussian Splatting from a Single Image
We then develop a panoramic depth estimation approach to calculate geometric information from panorama, and we combine geometric information with high-fidelity panoramic image to train an initial 3D Gaussian Splatting (3DGS) model.
EllieSQL: Cost-Efficient Text-to-SQL with Complexity-Aware Routing
Text-to-SQL automatically translates natural language queries to SQL, allowing non-technical users to retrieve data from databases without specialized SQL knowledge.
nvBench 2.0: A Benchmark for Natural Language to Visualization under Ambiguity
Natural Language to Visualization (NL2VIS) enables users to create visualizations from natural language queries, making data insights more accessible.
ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection
As the field of Multimodal Large Language Models (MLLMs) continues to evolve, their potential to revolutionize artificial intelligence is particularly promising, especially in addressing mathematical reasoning tasks.
DeformStream: Deformation-based Adaptive Volumetric Video Streaming
Volumetric video streaming offers immersive 3D experiences but faces significant challenges due to high bandwidth requirements and latency issues in transmitting detailed content in real time.
LLMCount: Enhancing Stationary mmWave Detection with Multimodal-LLM
By exploiting the decision-making capability of LLM, we can successfully compensate the signal power to acquire a uniform distribution and thereby achieve a detection with higher accuracy.
A Survey of NL2SQL with Large Language Models: Where are we, and where are we going?
Translating users' natural language queries (NL) into SQL queries (i. e., NL2SQL, a. k. a., Text-to-SQL) can significantly reduce barriers to accessing relational databases and support various commercial applications.
Are Large Language Models Good Statisticians?
Large Language Models (LLMs) have demonstrated impressive capabilities across a range of scientific tasks including mathematics, physics, and chemistry.
Efficient Deep Spiking Multi-Layer Perceptrons with Multiplication-Free Inference
As a result, we establish an efficient multi-stage spiking MLP network that blends effectively global receptive fields with local feature extraction for comprehensive spike-based computation.
PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations
In online adaptation phase, with the environment context inferred from few experiences collected in new environments, the policy is optimized by gradient ascent with respect to the PDVF.
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation
Discrete-continuous hybrid action space is a natural setting in many practical problems, such as robot control and game AI.
