:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Chaithra, Kadimisetty, Kamesh, Mohan, Biju R
Format:	Preprint
Publié:	2025
Sujets:	Artificial Intelligence
Accès en ligne:	https://arxiv.org/abs/2512.20082
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Lossy Image Compression -- A Frequent Sequence Mining perspective employing efficient Clustering
par: Kadimisetty, Avinash, et autres
Publié: (2026)

RAG-IT: Retrieval-Augmented Instruction Tuning for Automated Financial Analysis -- A Case Study for the Semiconductor Sector
par: To, Hai-Thien, et autres
Publié: (2024)

A Comparative Analysis of Instruction Fine-Tuning LLMs for Financial Text Classification
par: Fatemi, Sorouralsadat, et autres
Publié: (2024)

Predicting All-Cause Hospital Readmissions from Medical Claims Data of Hospitalised Patients
par: Kadimisetty, Avinash, et autres
Publié: (2025)

Comparing LLMs for Sentiment Analysis in Financial Market News
par: Teles, Lucas Eduardo Pereira, et autres
Publié: (2025)

Adaptive Signal Analysis for Automated Subsurface Defect Detection Using Impact Echo in Concrete Slabs
par: Pavurala, Deepthi, et autres
Publié: (2024)

Analogy-Driven Financial Chain-of-Thought (AD-FCoT): A Prompting Approach for Financial Sentiment Analysis
par: Singhal, Anmol Singhal Navya
Publié: (2025)

Fine-Tuning Gemma-7B for Enhanced Sentiment Analysis of Financial News Headlines
par: Mo, Kangtong, et autres
Publié: (2024)

Frequent Pattern Mining approach to Image Compression
par: Kadimisetty, Avinash, et autres
Publié: (2026)

AutoSearch: Adaptive Search Depth for Efficient Agentic RAG via Reinforcement Learning
par: Sun, Jingbo, et autres
Publié: (2026)

Self-Evolving LLMs via Continual Instruction Tuning
par: Kang, Jiazheng, et autres
Publié: (2025)

Evaluating Financial Sentiment Analysis with Annotators Instruction Assisted Prompting: Enhancing Contextual Interpretation and Stock Prediction Accuracy
par: Rahman, A M Muntasir, et autres
Publié: (2025)

A Deep Reinforcement Learning Approach for Adaptive Traffic Routing in Next-gen Networks
par: Abrol, Akshita, et autres
Publié: (2024)

A New Pipeline For Generating Instruction Dataset via RAG and Self Fine-Tuning
par: Song, Chih-Wei, et autres
Publié: (2024)

R3-RAG: Learning Step-by-Step Reasoning and Retrieval for LLMs via Reinforcement Learning
par: Li, Yuan, et autres
Publié: (2025)

Large Language Model Adaptation for Financial Sentiment Analysis
par: Inserte, Pau Rodriguez, et autres
Publié: (2024)

Dynamic Adaptive Optimization for Effective Sentiment Analysis Fine-Tuning on Large Language Models
par: Ding, Hongcheng, et autres
Publié: (2024)

HARLF: Hierarchical Reinforcement Learning and Lightweight LLM-Driven Sentiment Integration for Financial Portfolio Optimization
par: Coriat, Benjamin, et autres
Publié: (2025)

Pre-trained Large Language Models for Financial Sentiment Analysis
par: Luo, Wei, et autres
Publié: (2024)

LLMs for Explainable Business Decision-Making: A Reinforcement Learning Fine-Tuning Approach
par: Cheng, Xiang, et autres
Publié: (2025)

ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction Tuning
par: Wang, Xinyi, et autres
Publié: (2025)

Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases
par: Di Maio, Christian, et autres
Publié: (2024)

Efficient Differentially Private Fine-Tuning of LLMs via Reinforcement Learning
par: Khadangi, Afshin, et autres
Publié: (2025)

Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis
par: Vamvourellis, Dimitris, et autres
Publié: (2025)

RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions
par: Liu, Wanlong, et autres
Publié: (2024)

Jailbreak Instruction-Tuned LLMs via end-of-sentence MLP Re-weighting
par: Luo, Yifan, et autres
Publié: (2024)

Designing Heterogeneous LLM Agents for Financial Sentiment Analysis
par: Xing, Frank
Publié: (2024)

Advancing Robustness in Deep Reinforcement Learning with an Ensemble Defense Approach
par: Mohan, Adithya, et autres
Publié: (2025)

Teaching According to Talents! Instruction Tuning LLMs with Competence-Aware Curriculum Learning
par: Li, Yangning, et autres
Publié: (2025)

Fine-Tuning Causal LLMs for Text Classification: Embedding-Based vs. Instruction-Based Approaches
par: Yousefiramandi, Amirhossein, et autres
Publié: (2025)

Tuning LLMs by RAG Principles: Towards LLM-native Memory
par: Wei, Jiale, et autres
Publié: (2025)

A Curriculum Learning Approach to Reinforcement Learning: Leveraging RAG for Multimodal Question Answering
par: Zhang, Chenliang, et autres
Publié: (2025)

Rainbow Padding: Mitigating Early Termination in Instruction-Tuned Diffusion LLMs
par: Kim, Bumjun, et autres
Publié: (2025)

Are Large Language Models Good In-context Learners for Financial Sentiment Analysis?
par: Wei, Xinyu, et autres
Publié: (2025)

Scalable and Adaptive Parallel Training of Graph Transformer on Large Graphs
par: Lin, Jun-Liang, et autres
Publié: (2026)

GraphRAG-Router: Learning Cost-Efficient Routing over GraphRAGs and LLMs with Reinforcement Learning
par: Fan, Dongzhe, et autres
Publié: (2026)

Comparative Analysis of Pooling Mechanisms in LLMs: A Sentiment Analysis Perspective
par: Xing, Jinming, et autres
Publié: (2024)

ESSAM: A Novel Competitive Evolution Strategies Approach to Reinforcement Learning for Memory Efficient LLMs Fine-Tuning
par: Sun, Zhishen, et autres
Publié: (2026)

SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection
par: Liu, Liangxin, et autres
Publié: (2024)

Adaptive Task Balancing for Visual Instruction Tuning via Inter-Task Contribution and Intra-Task Difficulty
par: Dai, Yanqi, et autres
Publié: (2024)