Saved in:
| Main Authors: | Schaffelder, Max, Gatt, Albert |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.01490 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics
by: Du, Yupei, et al.
Published: (2023)
by: Du, Yupei, et al.
Published: (2023)
Context-aware Visual Storytelling with Visual Prefix Tuning and Contrastive Learning
by: Song, Yingjin, et al.
Published: (2024)
by: Song, Yingjin, et al.
Published: (2024)
Evaluating LLM-Generated Versus Human-Authored Responses in Role-Play Dialogues
by: Lu, Dongxu, et al.
Published: (2025)
by: Lu, Dongxu, et al.
Published: (2025)
Diverse and Fine-Grained Instruction-Following Ability Exploration with Synthetic Data
by: Gu, Zihui, et al.
Published: (2024)
by: Gu, Zihui, et al.
Published: (2024)
On the Diversity of Synthetic Data and its Impact on Training Large Language Models
by: Chen, Hao, et al.
Published: (2024)
by: Chen, Hao, et al.
Published: (2024)
VAQUUM: Are Vague Quantifiers Grounded in Visual Data?
by: Wong, Hugh Mee, et al.
Published: (2025)
by: Wong, Hugh Mee, et al.
Published: (2025)
Measuring Lexical Diversity of Synthetic Data Generated through Fine-Grained Persona Prompting
by: Kambhatla, Gauri, et al.
Published: (2025)
by: Kambhatla, Gauri, et al.
Published: (2025)
LLM for Barcodes: Generating Diverse Synthetic Data for Identity Documents
by: Patel, Hitesh Laxmichand, et al.
Published: (2024)
by: Patel, Hitesh Laxmichand, et al.
Published: (2024)
Morphological Analysis for the Maltese Language: The Challenges of a Hybrid System
by: Borg, Claudia, et al.
Published: (2017)
by: Borg, Claudia, et al.
Published: (2017)
A Systematic Analysis of Large Language Models as Soft Reasoners: The Case of Syllogistic Inferences
by: Bertolazzi, Leonardo, et al.
Published: (2024)
by: Bertolazzi, Leonardo, et al.
Published: (2024)
CV-Probes: Studying the interplay of lexical and world knowledge in visually grounded verb understanding
by: Beňová, Ivana, et al.
Published: (2024)
by: Beňová, Ivana, et al.
Published: (2024)
Probing Omissions and Distortions in Transformer-based RDF-to-Text Models
by: Faille, Juliette, et al.
Published: (2024)
by: Faille, Juliette, et al.
Published: (2024)
GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation
by: Chen, Zihong, et al.
Published: (2025)
by: Chen, Zihong, et al.
Published: (2025)
Synthetic Dataset Creation and Fine-Tuning of Transformer Models for Question Answering in Serbian
by: Cvetanović, Aleksa, et al.
Published: (2024)
by: Cvetanović, Aleksa, et al.
Published: (2024)
Domain-Adaptation through Synthetic Data: Fine-Tuning Large Language Models for German Law
by: Bashir, Ali Hamza, et al.
Published: (2026)
by: Bashir, Ali Hamza, et al.
Published: (2026)
Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models
by: Kaddour, Jean, et al.
Published: (2023)
by: Kaddour, Jean, et al.
Published: (2023)
From Image Captioning to Visual Storytelling
by: Passadakis, Admitos, et al.
Published: (2025)
by: Passadakis, Admitos, et al.
Published: (2025)
Configurable Preference Tuning with Rubric-Guided Synthetic Data
by: Gallego, Víctor
Published: (2025)
by: Gallego, Víctor
Published: (2025)
Grounded Misunderstandings in Asymmetric Dialogue: A Perspectivist Annotation Scheme for MapTask
by: Li, Nan, et al.
Published: (2025)
by: Li, Nan, et al.
Published: (2025)
Contrast Is All You Need
by: Kilic, Burak, et al.
Published: (2023)
by: Kilic, Burak, et al.
Published: (2023)
How and where does CLIP process negation?
by: Quantmeyer, Vincent, et al.
Published: (2024)
by: Quantmeyer, Vincent, et al.
Published: (2024)
When Models Decide and When They Bind: A Two-Stage Computation for Multiple-Choice Question-Answering
by: Wong, Hugh Mee, et al.
Published: (2026)
by: Wong, Hugh Mee, et al.
Published: (2026)
Measuring Diversity in Synthetic Datasets
by: Zhu, Yuchang, et al.
Published: (2025)
by: Zhu, Yuchang, et al.
Published: (2025)
LLaVA-Video: Video Instruction Tuning With Synthetic Data
by: Zhang, Yuanhan, et al.
Published: (2024)
by: Zhang, Yuanhan, et al.
Published: (2024)
CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation Data
by: Hong, Kung Yin, et al.
Published: (2024)
by: Hong, Kung Yin, et al.
Published: (2024)
LatteCLIP: Unsupervised CLIP Fine-Tuning via LMM-Synthetic Texts
by: Cao, Anh-Quan, et al.
Published: (2024)
by: Cao, Anh-Quan, et al.
Published: (2024)
DP-RFT: Learning to Generate Synthetic Text via Differentially Private Reinforcement Fine-Tuning
by: Xu, Fangyuan, et al.
Published: (2026)
by: Xu, Fangyuan, et al.
Published: (2026)
Configurable Safety Tuning of Language Models with Synthetic Preference Data
by: Gallego, Victor
Published: (2024)
by: Gallego, Victor
Published: (2024)
What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning
by: Zhu, Yuchang, et al.
Published: (2025)
by: Zhu, Yuchang, et al.
Published: (2025)
Linguistic and Argument Diversity in Synthetic Data for Function-Calling Agents
by: Greenstein, Dan, et al.
Published: (2026)
by: Greenstein, Dan, et al.
Published: (2026)
Repurposing Synthetic Data for Fine-grained Search Agent Supervision
by: Zhao, Yida, et al.
Published: (2025)
by: Zhao, Yida, et al.
Published: (2025)
Don't Learn, Ground: A Case for Natural Language Inference with Visual Grounding
by: Ignatev, Daniil, et al.
Published: (2025)
by: Ignatev, Daniil, et al.
Published: (2025)
References Matter: Investigating the Impact of Reference Set Variation on Summarization Evaluation
by: Casola, Silvia, et al.
Published: (2025)
by: Casola, Silvia, et al.
Published: (2025)
SyntheT2C: Generating Synthetic Data for Fine-Tuning Large Language Models on the Text2Cypher Task
by: Zhong, Ziije, et al.
Published: (2024)
by: Zhong, Ziije, et al.
Published: (2024)
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
by: Li, Haoran, et al.
Published: (2024)
by: Li, Haoran, et al.
Published: (2024)
Few-shot LLM Synthetic Data with Distribution Matching
by: Ren, Jiyuan, et al.
Published: (2025)
by: Ren, Jiyuan, et al.
Published: (2025)
CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning
by: Zhu, Xinyu, et al.
Published: (2026)
by: Zhu, Xinyu, et al.
Published: (2026)
Embedding-Driven Diversity Sampling to Improve Few-Shot Synthetic Data Generation
by: Lopez, Ivan, et al.
Published: (2025)
by: Lopez, Ivan, et al.
Published: (2025)
Common Objects Out of Context (COOCo): Investigating Multimodal Context and Semantic Scene Violations in Referential Communication
by: Merlo, Filippo, et al.
Published: (2025)
by: Merlo, Filippo, et al.
Published: (2025)
Burn After Reading: Do Multimodal Large Language Models Truly Capture Order of Events in Image Sequences?
by: Song, Yingjin, et al.
Published: (2025)
by: Song, Yingjin, et al.
Published: (2025)
Similar Items
-
FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics
by: Du, Yupei, et al.
Published: (2023) -
Context-aware Visual Storytelling with Visual Prefix Tuning and Contrastive Learning
by: Song, Yingjin, et al.
Published: (2024) -
Evaluating LLM-Generated Versus Human-Authored Responses in Role-Play Dialogues
by: Lu, Dongxu, et al.
Published: (2025) -
Diverse and Fine-Grained Instruction-Following Ability Exploration with Synthetic Data
by: Gu, Zihui, et al.
Published: (2024) -
On the Diversity of Synthetic Data and its Impact on Training Large Language Models
by: Chen, Hao, et al.
Published: (2024)