Imagen de Portada

DORA Explorer: Improving the Exploration Ability of LLMs Without Training

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gurjar, Priya, Ishmam, Md Farhan, Marino, Kenneth
Formato:	Preprint
Publicado:	2026
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

TimeWarp: Evaluating Web Agents by Revisiting the Past
por: Ishmam, Md Farhan, et al.
Publicado: (2026)

Diversity of Thought Improves Reasoning Abilities of LLMs
por: Naik, Ranjita, et al.
Publicado: (2023)

Improving LLM Abilities in Idiomatic Translation
por: Donthi, Sundesh, et al.
Publicado: (2024)

Enhancing Reasoning Abilities of Small LLMs with Cognitive Alignment
por: Cai, Wenrui, et al.
Publicado: (2025)

FourierKAN outperforms MLP on Text Classification Head Fine-tuning
por: Imran, Abdullah Al, et al.
Publicado: (2024)

Reasoning Does Not Necessarily Improve Role-Playing Ability
por: Feng, Xiachong, et al.
Publicado: (2025)

Evaluating the Pre-Consultation Ability of LLMs using Diagnostic Guidelines
por: Seo, Jean, et al.
Publicado: (2026)

Rethinking the Understanding Ability across LLMs through Mutual Information
por: Wang, Shaojie, et al.
Publicado: (2025)

PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs
por: Liu, An, et al.
Publicado: (2024)

Slimming Down LLMs Without Losing Their Minds
por: Qingda, et al.
Publicado: (2025)

Perceived Political Bias in LLMs Reduces Persuasive Abilities
por: DiGiuseppe, Matthew, et al.
Publicado: (2026)

Unleashing Embodied Task Planning Ability in LLMs via Reinforcement Learning
por: Fei, Zhaoye, et al.
Publicado: (2025)

Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension Ability
por: Han, Yujin, et al.
Publicado: (2024)

AudioChatLlama: Towards General-Purpose Speech Abilities for LLMs
por: Fathullah, Yassir, et al.
Publicado: (2023)

Code Pretraining Improves Entity Tracking Abilities of Language Models
por: Kim, Najoung, et al.
Publicado: (2024)

How Far Are We on the Decision-Making of LLMs? Evaluating LLMs' Gaming Ability in Multi-Agent Environments
por: Huang, Jen-tse, et al.
Publicado: (2024)

Can LLMs Reliably Simulate Real Students' Abilities in Mathematics and Reading Comprehension?
por: Srivatsa, KV Aditya, et al.
Publicado: (2025)

Diverse and Fine-Grained Instruction-Following Ability Exploration with Synthetic Data
por: Gu, Zihui, et al.
Publicado: (2024)

Fine-tuned Large Language Models (LLMs): Improved Prompt Injection Attacks Detection
por: Rahman, Md Abdur, et al.
Publicado: (2024)

BenHalluEval: A Multi-Task Hallucination Evaluation Framework for Large Language Models on Bengali
por: Adib, Shefayat E Shams, et al.
Publicado: (2026)

Logit Arithmetic Elicits Long Reasoning Capabilities Without Training
por: Zhang, Yunxiang, et al.
Publicado: (2025)

Dual-objective Language Models: Training Efficiency Without Overfitting
por: Samuel, David, et al.
Publicado: (2025)

Enhancing the Medical Context-Awareness Ability of LLMs via Multifaceted Self-Refinement Learning
por: Zhou, Yuxuan, et al.
Publicado: (2025)

Which LLMs Get the Joke? Probing Non-STEM Reasoning Abilities with HumorBench
por: Narad, Reuben, et al.
Publicado: (2025)

Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration
por: Pan, Yicheng, et al.
Publicado: (2025)

TactfulToM: Do LLMs Have the Theory of Mind Ability to Understand White Lies?
por: Liu, Yiwei, et al.
Publicado: (2025)

Continuous Approximations for Improving Quantization Aware Training of LLMs
por: Li, He, et al.
Publicado: (2024)

Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training
por: Yuan, Youliang, et al.
Publicado: (2024)

GRAFT: A Graph-based Flow-aware Agentic Framework for Document-level Machine Translation
por: Dutta, Himanshu, et al.
Publicado: (2025)

Reasoning LLMs are Wandering Solution Explorers
por: Lu, Jiahao, et al.
Publicado: (2025)

Distilling LLMs' Decomposition Abilities into Compact Language Models
por: Tarasov, Denis, et al.
Publicado: (2024)

Distilling an End-to-End Voice Assistant Without Instruction Training Data
por: Held, William, et al.
Publicado: (2024)

Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts
por: Nguyen, Xuan-Phi, et al.
Publicado: (2023)

Morphemes Without Borders: Evaluating Root-Pattern Morphology in Arabic Tokenizers and LLMs
por: Alakeel, Yara, et al.
Publicado: (2026)

ZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities
por: Dong, Wenhan, et al.
Publicado: (2025)

Is Depth All You Need? An Exploration of Iterative Reasoning in LLMs
por: Wu, Zongqian, et al.
Publicado: (2025)

From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunities
por: Ishmam, Md Farhan, et al.
Publicado: (2023)

CompoST: A Benchmark for Analyzing the Ability of LLMs To Compositionally Interpret Questions in a QALD Setting
por: Schmidt, David Maria, et al.
Publicado: (2025)

An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning
por: Chen, Zui, et al.
Publicado: (2024)

Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
por: Liu, Yijun, et al.
Publicado: (2024)