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Found 12 papers, 5 papers with code
Investigating Personalized Driving Behaviors in Dilemma Zones: Analysis and Prediction of Stop-or-Go Decisions
The results show that the Personalized Transformer Encoder improves the accuracy of predicting driver decision-making in the dilemma zone by 3. 7% to 12. 6% compared to the Generic Transformer Encoder, and by 16. 8% to 21. 6% over the binary logistic regression model.
Benchmarking and Improving Generator-Validator Consistency of Language Models
To improve the consistency of LMs, we propose to finetune on the filtered generator and validator responses that are GV-consistent, and call this approach consistency fine-tuning.
Color Me Intrigued: Quantifying Usage of Colors in Fiction
We present preliminary results in quantitative analyses of color usage in selected authors' works from LitBank.
Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference
While large pre-trained language models are powerful, their predictions often lack logical consistency across test inputs.
Systematicity in GPT-3's Interpretation of Novel English Noun Compounds
However, this evidence is consistent with GPT3 reasoning only about specific lexical items rather than the more abstract conceptual categories of Levin et al.'s theory.
When can I Speak? Predicting initiation points for spoken dialogue agents
Current spoken dialogue systems initiate their turns after a long period of silence (700-1000ms), which leads to little real-time feedback, sluggish responses, and an overall stilted conversational flow.
Learning Efficient Representations for Enhanced Object Detection on Large-scene SAR Images
It is a challenging problem to detect and recognize targets on complex large-scene Synthetic Aperture Radar (SAR) images.
Inferring the Reader: Guiding Automated Story Generation with Commonsense Reasoning
Transformer-based language model approaches to automated story generation currently provide state-of-the-art results.
Growing 3D Artefacts and Functional Machines with Neural Cellular Automata
Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells.
Automatic Story Generation: Challenges and Attempts
The scope of this survey paper is to explore the challenges in automatic story generation.
Reducing Non-Normative Text Generation from Language Models
Our normative fine-tuning technique is able to reduce non-normative text by 27-61%, depending on the data set.
Adaptable Human Intention and Trajectory Prediction for Human-Robot Collaboration
The effectiveness and flexibility of the proposed method has been validated in experiments.
Robotics
