Results 101 to 110 of about 52,458 (341)
The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?
Advanced Robotics Research, EarlyView.Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley +1 more source
Automated Assessment of Inferences Using Pre-Trained Language Models
Applied SciencesInference plays a key role in reading comprehension. However, assessing inference in reading is a complex process that relies on the judgment of trained experts. In this study, we explore objective and automated methods for assessing inference in readers’
Yongseok Yoo
doaj +1 more source
Sequence-to-Sequence Text Generation with Discrete Diffusion Models [PDF]
Jisuanji kexue yu tansuoDiffusion language models are currently the most promising language models among non-autoregressive models, and are expected to replace autoregressive language models, which suffer from slow inference speed, to achieve efficient and quality-preserving ...
JIANG Hang, CAI Guoyong, LI Sihui
doaj +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
Advanced Robotics Research, EarlyView.A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source
On Reference (In-)Determinacy in Natural Language Inference
Findings of the Association for Computational Linguistics: NAACL 2025We revisit the reference determinacy (RD) assumption in the task of natural language inference (NLI), i.e., the premise and hypothesis are assumed to refer to the same context when human raters annotate a label. While RD is a practical assumption for constructing a new NLI dataset, we observe that current NLI models, which are typically trained solely ...
Sihao Chen +6 more
openaire +2 more sources
Using Neural Networks to Generate Inferential Roles for Natural Language
Frontiers in Psychology, 2018 Neural networks have long been used to study linguistic phenomena spanning the domains of phonology, morphology, syntax, and semantics. Of these domains, semantics is somewhat unique in that there is little clarity concerning what a model needs to be ...
Peter Blouw, Chris Eliasmith
doaj +1 more source
LLM‐Integrated Human–Robot Interaction System for Microrobots
Advanced Robotics Research, EarlyView.This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source
Improving Distantly Supervised Document-Level Relation Extraction Through Natural Language Inference [PDF]
, 2022 Clara Vania +1 more
openalex +1 more source
Scientific Reasoning Is Material Inference: Combining Confirmation, Discovery, and Explanation [PDF]
, 2009 Whereas an inference (deductive as well as inductive) is usually viewed as being valid in virtue of its argument form, the present paper argues that scientific reasoning is material inference, i.e., justified in virtue of its content.
Brigandt, Ingo
core
Learning Fair Contextualized Word Representations with Natural Language Inference
, 2022 Contextualized word representations are the keystone of modern natural language processing. However, the fact that these representations encode latent stereotypes has given rise to much scientific concern, particularly as language models trained on these
He, Jacqueline
core