Search Results for author:
Found 15 papers, 9 papers with code
RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios
We introduce RESIN-11, a new schema-guided event extraction&prediction framework that can be applied to a large variety of newsworthy scenarios.
NDH-Full: Learning and Evaluating Navigational Agents on Full-Length Dialogue
In this paper, we explore the Navigation from Dialogue History (NDH) task, which is based on the Cooperative Vision-and-Dialogue Navigation (CVDN) dataset, and present a state-of-the-art model which is built upon Vision-Language transformers.
Collective Critics for Creative Story Generation
Generating a long story of several thousand words with narrative coherence using Large Language Models (LLMs) has been a challenging task.
Mixed-Session Conversation with Egocentric Memory
Recently introduced dialogue systems have demonstrated high usability.
Response Tuning: Aligning Large Language Models without Instruction
Our findings illuminate the role of establishing an adequate output space in alignment, highlighting the potential of the extensive inherent capabilities of pre-trained LLMs.
Conversation Chronicles: Towards Diverse Temporal and Relational Dynamics in Multi-Session Conversations
In this paper, we introduce a new 1M multi-session dialogue dataset, called Conversation Chronicles, for implementing a long-term conversation setup in which time intervals and fine-grained speaker relationships are incorporated.
CoSIm: Commonsense Reasoning for Counterfactual Scene Imagination
Next, a counterfactual imagined scene change (in textual form) is applied, and the model has to predict the new response to the initial question based on this scene change.
On the Limits of Evaluating Embodied Agent Model Generalization Using Validation Sets
Natural language guided embodied task completion is a challenging problem since it requires understanding natural language instructions, aligning them with egocentric visual observations, and choosing appropriate actions to execute in the environment to produce desired changes.
CAISE: Conversational Agent for Image Search and Editing
To our knowledge, this is the first dataset that provides conversational image search and editing annotations, where the agent holds a grounded conversation with users and helps them to search and edit images according to their requests.
Continuous Language Generative Flow
Recent years have witnessed various types of generative models for natural language generation (NLG), especially RNNs or transformer based sequence-to-sequence models, as well as variational autoencoder (VAE) and generative adversarial network (GAN) based models.
FixMyPose: Pose Correctional Captioning and Retrieval
During the correctional-captioning task, models must generate descriptions of how to move from the current to target pose image, whereas in the retrieval task, models should select the correct target pose given the initial pose and correctional description.
ArraMon: A Joint Navigation-Assembly Instruction Interpretation Task in Dynamic Environments
During this task, the agent (similar to a PokeMON GO player) is asked to find and collect different target objects one-by-one by navigating based on natural language instructions in a complex, realistic outdoor environment, but then also ARRAnge the collected objects part-by-part in an egocentric grid-layout environment.
Dense-Caption Matching and Frame-Selection Gating for Temporal Localization in VideoQA
Moreover, our model is also comprised of dual-level attention (word/object and frame level), multi-head self/cross-integration for different sources (video and dense captions), and gates which pass more relevant information to the classifier.
Modality-Balanced Models for Visual Dialogue
The Visual Dialog task requires a model to exploit both image and conversational context information to generate the next response to the dialogue.
Improving Visual Question Answering by Referring to Generated Paragraph Captions
These paragraph captions can hence contain substantial information of the image for tasks such as visual question answering.
