:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Marín, Javier
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	https://arxiv.org/abs/2510.21866
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Empirical Characterization of Temporal Constraint Processing in LLMs
by: Marín, Javier
Published: (2025)

LoRA-Augmented Generation (LAG) for Knowledge-Intensive Language Tasks
by: Fleshman, William, et al.
Published: (2025)

Breaking the Capability Ceiling of LLM Post-Training by Reintroducing Markov States
by: Yuan, Yurun, et al.
Published: (2026)

Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Task
by: Ranaldi, Leonardo, et al.
Published: (2025)

ALPINE: Unveiling the Planning Capability of Autoregressive Learning in Language Models
by: Wang, Siwei, et al.
Published: (2024)

Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks
by: Yuen, Sizhe, et al.
Published: (2025)

Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
by: Zhao, James Xu, et al.
Published: (2025)

Beyond Autoregression: An Empirical Study of Diffusion Large Language Models for Code Generation
by: Li, Chengze, et al.
Published: (2025)

Beyond Elicitation: Provision-based Prompt Optimization for Knowledge-Intensive Tasks
by: Xu, Yunzhe, et al.
Published: (2025)

Autoregressive Models for Knowledge Graph Generation
by: Thanapalasingam, Thiviyan, et al.
Published: (2026)

Reasoning Capabilities of Large Language Models on Dynamic Tasks
by: Wong, Annie, et al.
Published: (2025)

An Empirical Study on Capability of Large Language Models in Understanding Code Semantics
by: Nguyen, Thu-Trang, et al.
Published: (2024)

The Depth Ceiling: On the Limits of Large Language Models in Discovering Latent Planning
by: Xu, Yi, et al.
Published: (2026)

APE: Selective Fine-tuning with Acceptance Criteria for Language Model Adaptation
by: Marín, Javier
Published: (2025)

An Empirical Study of Knowledge Distillation for Code Understanding Tasks
by: Wang, Ruiqi, et al.
Published: (2025)

A non-ergodic framework for understanding emergent capabilities in Large Language Models
by: Marín, Javier
Published: (2025)

Towards Building a Robust Knowledge Intensive Question Answering Model with Large Language Models
by: Hong, Xingyun, et al.
Published: (2024)

Knowledge-Driven Hallucination in Large Language Models: An Empirical Study on Process Modeling
by: Kourani, Humam, et al.
Published: (2025)

LLaMA Beyond English: An Empirical Study on Language Capability Transfer
by: Zhao, Jun, et al.
Published: (2024)

Controllable and Reliable Knowledge-Intensive Task-Oriented Conversational Agents with Declarative Genie Worksheets
by: Joshi, Harshit, et al.
Published: (2024)

KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning
by: Yu, Peng, et al.
Published: (2024)

Evaluating Large Language Models for Abstract Evaluation Tasks: An Empirical Study
by: Liu, Yinuo, et al.
Published: (2026)

Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks
by: Wu, Zhaofeng, et al.
Published: (2023)

Knowledge-Intensive Video Generation
by: Wang, Chenxu, et al.
Published: (2026)

Unsolvability Ceiling in Multi-LLM Routing: An Empirical Study of Evaluation Artifacts
by: Garg, Saloni, et al.
Published: (2026)

An Empirical Study of Autoregressive Pre-training from Videos
by: Rajasegaran, Jathushan, et al.
Published: (2025)

KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA
by: Su, Xiaorui, et al.
Published: (2024)

Process Reward Agents for Steering Knowledge-Intensive Reasoning
by: Sohn, Jiwoong, et al.
Published: (2026)

Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence
by: Ren, Wanying, et al.
Published: (2026)

CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks
by: Feng, Jie, et al.
Published: (2024)

Enhancing the Capabilities of Large Language Models for API calls through Knowledge Graphs
by: Yang, Ye, et al.
Published: (2025)

FoundaBench: Evaluating Chinese Fundamental Knowledge Capabilities of Large Language Models
by: Li, Wei, et al.
Published: (2024)

Knowledge Graph Structure as Prompt: Improving Small Language Models Capabilities for Knowledge-based Causal Discovery
by: Susanti, Yuni, et al.
Published: (2024)

Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trap
by: Tanna, Aditya, et al.
Published: (2026)

Diagnosing Spectral Ceilings in Equivariant Neural Force Fields
by: Kim, Hyunmog
Published: (2026)

Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion
by: Huang, ShiYing, et al.
Published: (2026)

WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?
by: Drouin, Alexandre, et al.
Published: (2024)

Continuous Autoregressive Language Models
by: Shao, Chenze, et al.
Published: (2025)

Automated Interpretability and Feature Discovery in Language Models with Agents
by: Marin-Llobet, Arnau, et al.
Published: (2026)

Small Models, Big Tasks: An Exploratory Empirical Study on Small Language Models for Function Calling
by: Kavathekar, Ishan, et al.
Published: (2025)