Copertina

CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervision

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ito, Aoi, Dohi, Kota, Kawaguchi, Yohei
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computation and Language Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Domain-Independent Automatic Generation of Descriptive Texts for Time-Series Data
di: Dohi, Kota, et al.
Pubblicazione: (2024)

Can VLM Pseudo-Labels Train a Time-Series QA Model That Outperforms the VLM?
di: Fujimura, Takuya, et al.
Pubblicazione: (2025)

Retrieving Time-Series Differences Using Natural Language Queries
di: Dohi, Kota, et al.
Pubblicazione: (2025)

Distributed collaborative anomalous sound detection by embedding sharing
di: Dohi, Kota, et al.
Pubblicazione: (2024)

DiffNator: Generating Structured Explanations of Time-Series Differences
di: Dohi, Kota, et al.
Pubblicazione: (2025)

LaSTR: Language-Driven Time-Series Segment Retrieval
di: Dohi, Kota, et al.
Pubblicazione: (2026)

CLaC at SemEval-2026 Task 6: Response Clarity Detection in Political Discourse
di: Turk, Nawar, et al.
Pubblicazione: (2026)

Can We Estimate Purchase Intention Based on Zero-shot Speech Emotion Recognition?
di: Nagase, Ryotaro, et al.
Pubblicazione: (2024)

MIMII-Agent: Leveraging LLMs with Function Calling for Relative Evaluation of Anomalous Sound Detection
di: Purohit, Harsh, et al.
Pubblicazione: (2025)

Can Language Models Learn Typologically Implausible Languages?
di: Xu, Tianyang, et al.
Pubblicazione: (2025)

Naturally Supervised 3D Visual Grounding with Language-Regularized Concept Learners
di: Feng, Chun, et al.
Pubblicazione: (2024)

Synergizing Unsupervised and Supervised Learning: A Hybrid Approach for Accurate Natural Language Task Modeling
di: Talukdar, Wrick, et al.
Pubblicazione: (2024)

ViCLSR: A Supervised Contrastive Learning Framework with Natural Language Inference for Natural Language Understanding Tasks
di: Van Huynh, Tin, et al.
Pubblicazione: (2026)

Investigating Layer Importance in Large Language Models
di: Zhang, Yang, et al.
Pubblicazione: (2024)

Time Series Language Model for Descriptive Caption Generation
di: Trabelsi, Mohamed, et al.
Pubblicazione: (2025)

Learning Machines: In Search of a Concept Oriented Language
di: Gunes, Veyis
Pubblicazione: (2024)

CLaP -- State Detection from Time Series
di: Ermshaus, Arik, et al.
Pubblicazione: (2025)

AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
di: Liu, Yong, et al.
Pubblicazione: (2024)

SIEVE: Sample-Efficient Parametric Learning from Natural Language
di: Asawa, Parth, et al.
Pubblicazione: (2026)

Self-Supervised Time-Series Anomaly Detection Using Learnable Data Augmentation
di: Choi, Kukjin, et al.
Pubblicazione: (2024)

Concept Bottleneck Large Language Models
di: Sun, Chung-En, et al.
Pubblicazione: (2024)

Leveraging Large Language Models for Structure Learning in Prompted Weak Supervision
di: Su, Jinyan, et al.
Pubblicazione: (2024)

MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning
di: Ye, Jiexia, et al.
Pubblicazione: (2024)

Natural Language Actor-Critic: Scalable Off-Policy Learning in Language Space
di: Hong, Joey, et al.
Pubblicazione: (2025)

Towards Compositionality in Concept Learning
di: Stein, Adam, et al.
Pubblicazione: (2024)

LLM-PS: Empowering Large Language Models for Time Series Forecasting with Temporal Patterns and Semantics
di: Tang, Jialiang, et al.
Pubblicazione: (2025)

Natural Language Reinforcement Learning
di: Feng, Xidong, et al.
Pubblicazione: (2024)

Natural Language Reinforcement Learning
di: Feng, Xidong, et al.
Pubblicazione: (2024)

Large Language Models for Time Series: A Survey
di: Zhang, Xiyuan, et al.
Pubblicazione: (2024)

Analyzing Persuasive Strategies in Meme Texts: A Fusion of Language Models with Paraphrase Enrichment
di: Nayak, Kota Shamanth Ramanath, et al.
Pubblicazione: (2024)

Cross-Refine: Improving Natural Language Explanation Generation by Learning in Tandem
di: Wang, Qianli, et al.
Pubblicazione: (2024)

Mathematical Reasoning via Intervention-Based Time-Series Causal Discovery Using LLMs as Concept Mastery Simulators
di: Okita, Tsuyoshi
Pubblicazione: (2026)

Safe Reinforcement Learning with Free-form Natural Language Constraints and Pre-Trained Language Models
di: Lou, Xingzhou, et al.
Pubblicazione: (2024)

Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness
di: Liang, Zihan, et al.
Pubblicazione: (2026)

Hierarchical Concept Geometry in Language Models Emerges from Word Co-occurrence
di: Nava, Andres, et al.
Pubblicazione: (2026)

Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis
di: Liu, Haoxin, et al.
Pubblicazione: (2024)

Assessing the Applicability of Natural Language Processing to Traditional Social Science Methodology: A Case Study in Identifying Strategic Signaling Patterns in Presidential Directives
di: LeMay, C., et al.
Pubblicazione: (2025)

Text2TimeSeries: Enhancing Financial Forecasting through Time Series Prediction Updates with Event-Driven Insights from Large Language Models
di: Kurisinkel, Litton Jose, et al.
Pubblicazione: (2024)

Scaffolded Language Models with Language Supervision for Mixed-Autonomy: A Survey
di: Lin, Matthieu, et al.
Pubblicazione: (2024)

Plan Optimization to Bilingual Dictionary Induction for Low-Resource Language Families
di: Nasution, Arbi Haza, et al.
Pubblicazione: (2020)