Search Results for author:
Found 11 papers, 5 papers with code
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
We present a new algorithm that significantly improves the efficiency of exploration for deep Q-learning agents in dialogue systems.
Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access
In this paper, we address this limitation by replacing symbolic queries with an induced "soft" posterior distribution over the KB that indicates which entities the user is interested in.
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
We present a new algorithm that significantly improves the efficiency of exploration for deep Q-learning agents in dialogue systems.
UNITER: UNiversal Image-TExt Representation Learning
Different from previous work that applies joint random masking to both modalities, we use conditional masking on pre-training tasks (i. e., masked language/region modeling is conditioned on full observation of image/text).
Ranked #3 on
Visual Question Answering (VQA)
on VCR (Q-A) test
UNITER: Learning UNiversal Image-TExt Representations
Joint image-text embedding is the bedrock for most Vision-and-Language (V+L) tasks, where multimodality inputs are jointly processed for visual and textual understanding.
UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language Modeling
On grounded captioning, UniTAB presents a simpler solution with a single output head, and significantly outperforms state of the art in both grounding and captioning evaluations.
SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning
Based on this model architecture, we show that video captioning can benefit significantly from more densely sampled video frames as opposed to previous successes with sparsely sampled video frames for video-and-language understanding tasks (e. g., video question answering).
MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action
We propose MM-REACT, a system paradigm that integrates ChatGPT with a pool of vision experts to achieve multimodal reasoning and action.
Ranked #22 on
Visual Question Answering
on MM-Vet
Towards Zero-power 3D Imaging: VLC-assisted Passive ToF Sensing
Passive Time-of-Flight (ToF) imaging can be enabled by optical wireless communication (OWC).
MM-VID: Advancing Video Understanding with GPT-4V(ision)
We present MM-VID, an integrated system that harnesses the capabilities of GPT-4V, combined with specialized tools in vision, audio, and speech, to facilitate advanced video understanding.
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classification
Federated Learning (FL) has garnered significant interest recently due to its potential as an effective solution for tackling many challenges in diverse application scenarios, for example, data privacy in network edge traffic classification.
