Copertina

Boosting Accuracy & Efficiency: Teaching LLMs to "Know When to Stop" with Absolute Quality Assessment

Fuente: Zenodo

Salvato in:

Dettagli Bibliografici
Autori principali:	Etsuro, Minami, Michael, Mak, Safia, Bendjebar, Daniel, Kirste
Natura:	Recurso digital
Pubblicazione:	Zenodo 2025
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Capability Self-Assessment: Teaching LLMs to Know Their Limits
di: Yang, Haoyan, et al.
Pubblicazione: (2026)

Does Your Reasoning Model Implicitly Know When to Stop Thinking?
di: Huang, Zixuan, et al.
Pubblicazione: (2026)

Know When To Stop: A Study of Semantic Drift in Text Generation
di: Spataru, Ava, et al.
Pubblicazione: (2024)

CaRT: Teaching LLM Agents to Know When They Know Enough
di: Liu, Grace, et al.
Pubblicazione: (2025)

Knowing When to Stop: Efficient Context Processing via Latent Sufficiency Signals
di: Xie, Roy, et al.
Pubblicazione: (2025)

Knowing When to Stop: Delay-Adaptive Spiking Neural Network Classifiers with Reliability Guarantees
di: Chen, Jiechen, et al.
Pubblicazione: (2023)

Boosting Accuracy and Efficiency of Budget Forcing in LLMs via Reinforcement Learning for Mathematical Reasoning
di: Tarunokusumo, Ravindra Aribowo, et al.
Pubblicazione: (2025)

Beyond Accuracy: Decomposing the Reasoning Efficiency of LLMs
di: Kaiser, Daniel, et al.
Pubblicazione: (2026)

Identity Infrastructure for Autonomous AI Agents: Threat Model, Requirements, and Reference Architecture
di: Kirste, Daniel, et al.
Pubblicazione: (2026)

Knowing When to Stop Matters: A Unified Algorithm for Online Conversion under Horizon Uncertainty
di: Wang, Yanzhao, et al.
Pubblicazione: (2025)

VLAA-GUI: Knowing When to Stop, Recover, and Search, A Modular Framework for GUI Automation
di: Han, Qijun, et al.
Pubblicazione: (2026)

Draft Model Knows When to Stop: Self-Verification Speculative Decoding for Long-Form Generation
di: Zhang, Ziyin, et al.
Pubblicazione: (2024)

Improving Teaching Quality in Physical Education in China: A Comprehensive Analysis
di: Zhang Chao, et al.
Pubblicazione: (2026)

What and When Do They Know? Web-Based Assessment.
di: Samson, Sue
Pubblicazione: (2000)

Do LLMs Know What They Know? Measuring Metacognitive Efficiency with Signal Detection Theory
di: Cacioli, Jon-Paul
Pubblicazione: (2026)

Exploring Challenges Encountered by EFL Libyan Learners in Research Teaching and Writing
di: Alsied, Safia Mujtaba, et al.
Pubblicazione: (2017)

Web Site Quality: Do Students Know It When They See It?
di: Small, Ruth V., et al.
Pubblicazione: (1999)

LLMs Know When They Know, but Do Not Act on It: A Metacognitive Harness for Test-time Scaling
di: Cao, Qi, et al.
Pubblicazione: (2026)

Knowing When to Abstain: Medical LLMs Under Clinical Uncertainty
di: Machcha, Sravanthi, et al.
Pubblicazione: (2026)

Stop Starving or Stuffing Me: Boosting Firmware Fuzzing Efficiency with On-demand Input Delivery
di: Shen, Shandian, et al.
Pubblicazione: (2026)

Know When To Hold 'em, Know When To Fold 'em.
di: Jacso, Peter
Pubblicazione: (1999)

Explorations of the Softmax Space: Knowing When the Neural Network Doesn't Know
di: Sikar, Daniel, et al.
Pubblicazione: (2025)

Entanglement Distribution in the Quantum Internet: Knowing when to Stop!
di: Cacciapuoti, Angela Sara, et al.
Pubblicazione: (2023)

Comment on “Fiscal Projections and Debt Sustainability in Japan”
di: Etsuro Shioji
Pubblicazione: (2025)

When to Stop? Towards Efficient Code Generation in LLMs with Excess Token Prevention
di: Guo, Lianghong, et al.
Pubblicazione: (2024)

When Models Know When They Do Not Know: Calibration, Cascading, and Cleaning
di: Hao, Chenjie, et al.
Pubblicazione: (2026)

KnowRL: Teaching Language Models to Know What They Know
di: Kale, Sahil, et al.
Pubblicazione: (2025)

Absolute Technical Efficiency Indices
di: Larbi, Montacer Ben Cheikh, et al.
Pubblicazione: (2024)

Science is Subjective: Humans Are Incapable of Knowing or Discovering Absolute Truth
di: Aguilera Katayama, Kaoru
Pubblicazione: (2026)

When Good Teaching is Not Good Teaching
di: Michael G. Strawser
Pubblicazione: (2025)

TopicFM+: Boosting Accuracy and Efficiency of Topic-Assisted Feature Matching
di: Giang, Khang Truong, et al.
Pubblicazione: (2023)

"Knowing When You Don't Know": A Multilingual Relevance Assessment Dataset for Robust Retrieval-Augmented Generation
di: Thakur, Nandan, et al.
Pubblicazione: (2023)

Stop When Enough: Adaptive Early-Stopping for Chain-of-Thought Reasoning
di: Sun, Renliang, et al.
Pubblicazione: (2025)

Design of a Compact Dual Band Microstrip Antenna for Bluetooth/WLAN and UWB Applications
di: Safia Bibi
Pubblicazione: (2025)

When Models Know More Than They Say: Probing Analogical Reasoning in LLMs
di: McGovern, Hope, et al.
Pubblicazione: (2026)

Teaching Large Language Models When Not to Know: Learning Temporal Critique for Ex-Ante Reasoning
di: Ding, Chenlu, et al.
Pubblicazione: (2026)

Integrated Optoelectronic Mechanical, and Thermoelectric Properties of CsNdATe 3 (ACd, Zn) Quaternary Materials for High‐Efficiency Energy Conversion Applications
di: Safia Abdullah R. Alharbi, et al.
Pubblicazione: (2026)

When LLMs Stop Following Steps: A Diagnostic Study of Procedural Execution in Language Models
di: Panda, Sailesh, et al.
Pubblicazione: (2026)

When You Need to Know
di: Brown, Flora Morris
Pubblicazione: (1976)

Smart but Costly? Benchmarking LLMs on Functional Accuracy and Energy Efficiency
di: Mehditabar, Mohammadjavad, et al.
Pubblicazione: (2025)