Cover Image

Multi-Conditional Ranking with Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pezeshkpour, Pouya, Hruschka, Estevam
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AutoPyVerifier: Learning Compact Executable Verifiers for Large Language Model Outputs
by: Pezeshkpour, Pouya, et al.
Published: (2026)

From Task Solving to Robust Real-World Adaptation in LLM Agents
by: Pezeshkpour, Pouya, et al.
Published: (2026)

Learning Beyond the Surface: How Far Can Continual Pre-Training with LoRA Enhance LLMs' Domain-Specific Insight Learning?
by: Pezeshkpour, Pouya, et al.
Published: (2025)

Insight-RAG: Enhancing LLMs with Insight-Driven Augmentation
by: Pezeshkpour, Pouya, et al.
Published: (2025)

Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions
by: Pezeshkpour, Pouya, et al.
Published: (2024)

From Proof to Program: Characterizing Tool-Induced Reasoning Hallucinations in Large Language Models
by: Bayat, Farima Fatahi, et al.
Published: (2025)

Evaluating Bias in LLMs for Job-Resume Matching: Gender, Race, and Education
by: Iso, Hayate, et al.
Published: (2025)

Align then Train: Efficient Retrieval Adapter Learning
by: Maekawa, Seiji, et al.
Published: (2026)

Towards Reliable Benchmarking: A Contamination Free, Controllable Evaluation Framework for Multi-step LLM Function Calling
by: Maekawa, Seiji, et al.
Published: (2025)

Mixed Signals: Decoding VLMs' Reasoning and Underlying Bias in Vision-Language Conflict
by: Pezeshkpour, Pouya, et al.
Published: (2025)

Less is More for Long Document Summary Evaluation by LLMs
by: Wu, Yunshu, et al.
Published: (2023)

Geometry-Aware Decoding with Wasserstein-Regularized Truncation and Mass Penalties for Large Language Models
by: Davoodi, Arash Gholami, et al.
Published: (2026)

From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization
by: Belem, Catarina G., et al.
Published: (2024)

A Dynamic Self-Evolving Extraction System
by: Amin-Naseri, Moin, et al.
Published: (2026)

Verification-Aware Planning for Multi-Agent Systems
by: Xu, Tianyang, et al.
Published: (2025)

FactLens: Benchmarking Fine-Grained Fact Verification
by: Mitra, Kushan, et al.
Published: (2024)

LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs
by: Davoodi, Arash Gholami, et al.
Published: (2024)

Learning from Supervision with Semantic and Episodic Memory: A Reflective Approach to Agent Adaptation
by: Hassell, Jackson, et al.
Published: (2025)

Dynamic Rank Reinforcement Learning for Adaptive Low-Rank Multi-Head Self Attention in Large Language Models
by: Erden, Caner
Published: (2025)

Natural Language Processing for Human Resources: A Survey
by: Otani, Naoki, et al.
Published: (2024)

BoRA: Bayesian Hierarchical Low-Rank Adaption for Multi-Task Large Language Models
by: Eide, Simen, et al.
Published: (2024)

Prompt-Dependent Ranking of Large Language Models with Uncertainty Quantification
by: Menendez, Angel Rodrigo Avelar, et al.
Published: (2026)

Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks
by: Mishra, Aditi, et al.
Published: (2023)

LCQ: Low-Rank Codebook based Quantization for Large Language Models
by: Cai, Wen-Pu, et al.
Published: (2024)

ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals
by: Saxena, Utkarsh, et al.
Published: (2024)

FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing
by: Smith, James Seale, et al.
Published: (2025)

Found in the Middle: Permutation Self-Consistency Improves Listwise Ranking in Large Language Models
by: Tang, Raphael, et al.
Published: (2023)

Ranking Large Language Models without Ground Truth
by: Dhurandhar, Amit, et al.
Published: (2024)

Adaptive Feature-based Low-Rank Compression of Large Language Models via Bayesian Optimization
by: Ji, Yixin, et al.
Published: (2024)

LoLCATs: On Low-Rank Linearizing of Large Language Models
by: Zhang, Michael, et al.
Published: (2024)

Unsupervised Contrast-Consistent Ranking with Language Models
by: Stoehr, Niklas, et al.
Published: (2023)

Benchmarking Large Language Models for Persian: A Preliminary Study Focusing on ChatGPT
by: Abaskohi, Amirhossein, et al.
Published: (2024)

QDyLoRA: Quantized Dynamic Low-Rank Adaptation for Efficient Large Language Model Tuning
by: Rajabzadeh, Hossein, et al.
Published: (2024)

Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalization, and Information-Theoretic Guarantees
by: Soarez, Alberlucia Rafael, et al.
Published: (2026)

Multi-Reference Preference Optimization for Large Language Models
by: Le, Hung, et al.
Published: (2024)

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
by: Shi, Haizhou, et al.
Published: (2024)

BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models
by: Chang, Yupeng, et al.
Published: (2024)

Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting
by: Qin, Zhen, et al.
Published: (2023)

Memorize and Rank: Elevating Large Language Models for Clinical Diagnosis Prediction
by: Ma, Mingyu Derek, et al.
Published: (2025)

Multi-Bit Distortion-Free Watermarking for Large Language Models
by: Boroujeny, Massieh Kordi, et al.
Published: (2024)