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Found 7 papers, 6 papers with code
Empowering Graph Invariance Learning with Deep Spurious Infomax
To bridge this gap, we introduce a novel graph invariance learning paradigm, which induces a robust and general inductive bias.
MMAC-Copilot: Multi-modal Agent Collaboration Operating System Copilot
Autonomous virtual agents are often limited by their singular mode of interaction with real-world environments, restricting their versatility.
Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models
We have experimentally observed that LLMs possess the capability to understand the "confidence" in their own responses.
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process
Identifying the underlying time-delayed latent causal processes in sequential data is vital for grasping temporal dynamics and making downstream reasoning.
BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models
Large Multimodal Models (LMMs) such as GPT-4V and LLaVA have shown remarkable capabilities in visual reasoning with common image styles.
Ranked #1000000000 on
Visual Question Answering
on MS COCO
Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction
Specifically, we model the trajectory sampling as a Gaussian process and construct an acquisition function to measure the potential sampling value.
Multimodal Learning for Hateful Memes Detection
Memes are used for spreading ideas through social networks.
