Copertina

What's New in My Data? Novelty Exploration via Contrastive Generation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Isonuma, Masaru, Titov, Ivan
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Unlearning Traces the Influential Training Data of Language Models
di: Isonuma, Masaru, et al.
Pubblicazione: (2024)

Shared Doubt: Zero-shot Cross-Lingual Confidence Estimation for Language Models
di: Kyriakou, Athina, et al.
Pubblicazione: (2026)

Joint Localization and Activation Editing for Low-Resource Fine-Tuning
di: Lai, Wen, et al.
Pubblicazione: (2025)

Finding Culture-Sensitive Neurons in Vision-Language Models
di: Zhao, Xiutian, et al.
Pubblicazione: (2025)

UniDetox: Universal Detoxification of Large Language Models via Dataset Distillation
di: Lu, Huimin, et al.
Pubblicazione: (2025)

Scalpel vs. Hammer: GRPO Amplifies Existing Capabilities, SFT Replaces Them
di: Rajani, Neel, et al.
Pubblicazione: (2025)

What Is Wrong with My Model? Identifying Systematic Problems with Semantic Data Slicing
di: Yang, Chenyang, et al.
Pubblicazione: (2024)

SciMON: Scientific Inspiration Machines Optimized for Novelty
di: Wang, Qingyun, et al.
Pubblicazione: (2023)

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback
di: Hoang, Thai, et al.
Pubblicazione: (2025)

SAGE: A Novelty Gate for Efficient Memory Evolution in Agentic LLMs
di: Wang, Sijia, et al.
Pubblicazione: (2026)

Contrastive Decoding for Synthetic Data Generation in Low-Resource Language Modeling
di: Ulm, Jannek, et al.
Pubblicazione: (2025)

Towards Transfer Unlearning: Empirical Evidence of Cross-Domain Bias Mitigation
di: Lu, Huimin, et al.
Pubblicazione: (2024)

Be My Eyes: Extending Large Language Models to New Modalities Through Multi-Agent Collaboration
di: Huang, James Y., et al.
Pubblicazione: (2025)

Multi-Preference Optimization: Generalizing DPO via Set-Level Contrasts
di: Gupta, Taneesh, et al.
Pubblicazione: (2024)

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
di: Huang, Zeyu, et al.
Pubblicazione: (2025)

General Exploratory Bonus for Optimistic Exploration in RLHF
di: Li, Wendi, et al.
Pubblicazione: (2025)

Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems
di: Qi, Zhenting, et al.
Pubblicazione: (2024)

CLIPO: Contrastive Learning in Policy Optimization Generalizes RLVR
di: Cui, Sijia, et al.
Pubblicazione: (2026)

Steering Llama 2 via Contrastive Activation Addition
di: Panickssery, Nina, et al.
Pubblicazione: (2023)

Unlocking Reasoning Capabilities in LLMs via Reinforcement Learning Exploration
di: Deng, Wenhao, et al.
Pubblicazione: (2025)

Automated Capability Discovery via Foundation Model Self-Exploration
di: Lu, Cong, et al.
Pubblicazione: (2025)

Improving Word Translation via Two-Stage Contrastive Learning
di: Li, Yaoyiran, et al.
Pubblicazione: (2022)

CALRec: Contrastive Alignment of Generative LLMs for Sequential Recommendation
di: Li, Yaoyiran, et al.
Pubblicazione: (2024)

Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization
di: Du, Yihan, et al.
Pubblicazione: (2024)

Context-Enhanced Contrastive Search for Improved LLM Text Generation
di: Sen, Jaydip, et al.
Pubblicazione: (2025)

Efficient Process Reward Modeling via Contrastive Mutual Information
di: Lee, Nakyung, et al.
Pubblicazione: (2026)

Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation
di: Li, Ziniu, et al.
Pubblicazione: (2025)

POPE: Learning to Reason on Hard Problems via Privileged On-Policy Exploration
di: Qu, Yuxiao, et al.
Pubblicazione: (2026)

What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions
di: Choe, Sang Keun, et al.
Pubblicazione: (2024)

By My Eyes: Grounding Multimodal Large Language Models with Sensor Data via Visual Prompting
di: Yoon, Hyungjun, et al.
Pubblicazione: (2024)

Evaluating and Enhancing Large Language Models for Novelty Assessment in Scholarly Publications
di: Lin, Ethan, et al.
Pubblicazione: (2024)

CALICO: Conversational Agent Localization via Synthetic Data Generation
di: Rosenbaum, Andy, et al.
Pubblicazione: (2024)

Beyond Markovian: Reflective Exploration via Bayes-Adaptive RL for LLM Reasoning
di: Zhang, Shenao, et al.
Pubblicazione: (2025)

Deep Dense Exploration for LLM Reinforcement Learning via Pivot-Driven Resampling
di: Guo, Yiran, et al.
Pubblicazione: (2026)

CaLM: Contrasting Large and Small Language Models to Verify Grounded Generation
di: Hsu, I-Hung, et al.
Pubblicazione: (2024)

Active Layer-Contrastive Decoding Reduces Hallucination in Large Language Model Generation
di: Zhang, Hongxiang, et al.
Pubblicazione: (2025)

Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual Classification
di: Pecher, Branislav, et al.
Pubblicazione: (2026)

Rethinking Time Series Forecasting with LLMs via Nearest Neighbor Contrastive Learning
di: Bogahawatte, Jayanie, et al.
Pubblicazione: (2024)

Aligning Backchannel and Dialogue Context Representations via Contrastive LLM Fine-Tuning
di: Qian, Livia, et al.
Pubblicazione: (2026)

What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
di: Liu, Wei, et al.
Pubblicazione: (2023)