Copertina

MiMIC: Multi-Modal Indian Earnings Calls Dataset to Predict Stock Prices

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ghosh, Sohom, Maji, Arnab, Naskar, Sudip Kumar
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Experimenting with Multi-modal Information to Predict Success of Indian IPOs
di: Ghosh, Sohom, et al.
Pubblicazione: (2024)

BASIR: Budget-Assisted Sectoral Impact Ranking -- A Dataset for Sector Identification and Performance Prediction Using Language Models
di: Ghosh, Sohom, et al.
Pubblicazione: (2025)

BhashaSetu: Cross-Lingual Knowledge Transfer from High-Resource to Extreme Low-Resource Languages
di: Maji, Subhadip, et al.
Pubblicazione: (2026)

NyayaAnumana & INLegalLlama: The Largest Indian Legal Judgment Prediction Dataset and Specialized Language Model for Enhanced Decision Analysis
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2024)

MiMIC: Mitigating Visual Modality Collapse in Universal Multimodal Retrieval While Avoiding Semantic Misalignment
di: Li, Juan, et al.
Pubblicazione: (2026)

NyayaMind- A Framework for Transparent Legal Reasoning and Judgment Prediction in the Indian Legal System
di: Shukla, Parjanya Aditya, et al.
Pubblicazione: (2026)

Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2024)

Generalized Stock Price Prediction for Multiple Stocks Combined with News Fusion
di: Liao, Pei-Jun, et al.
Pubblicazione: (2026)

TathyaNyaya and FactLegalLlama: Advancing Factual Judgment Prediction and Explanation in the Indian Legal Context
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2025)

Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach
di: Ni, Haowei, et al.
Pubblicazione: (2024)

NyayaRAG: Realistic Legal Judgment Prediction with RAG under the Indian Common Law System
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2025)

LegalSeg: Unlocking the Structure of Indian Legal Judgments Through Rhetorical Role Classification
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2025)

API Pack: A Massive Multi-Programming Language Dataset for API Call Generation
di: Guo, Zhen, et al.
Pubblicazione: (2024)

Ayn: A Tiny yet Competitive Indian Legal Language Model Pretrained from Scratch
di: Niyogi, Mitodru, et al.
Pubblicazione: (2024)

ReGal: A First Look at PPO-based Legal AI for Judgment Prediction and Summarization in India
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2025)

Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks
di: Abdelaziz, Ibrahim, et al.
Pubblicazione: (2024)

Early Linguistic Pattern of Anxiety from Social Media Using Interpretable Linguistic Features: A Multi-Faceted Validation Study with Author-Disjoint Evaluation
di: Utsa, Arnab Das
Pubblicazione: (2026)

Efficient data selection employing Semantic Similarity-based Graph Structures for model training
di: Petcu, Roxana, et al.
Pubblicazione: (2024)

IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents
di: Mohanty, Shrestha, et al.
Pubblicazione: (2024)

Gradients Must Earn Their Influence: Unifying SFT with Generalized Entropic Objectives
di: Wang, Zecheng, et al.
Pubblicazione: (2026)

Can AI Freelancers Compete? Benchmarking Earnings, Reliability, and Task Success at Scale
di: Noever, David, et al.
Pubblicazione: (2025)

IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning
di: Joshi, Abhinav, et al.
Pubblicazione: (2024)

Rethinking Legal Judgement Prediction in a Realistic Scenario in the Era of Large Language Models
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2024)

MedAidDialog: A Multilingual Multi-Turn Medical Dialogue Dataset for Accessible Healthcare
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2026)

Structured Legal Document Generation in India: A Model-Agnostic Wrapper Approach with VidhikDastaavej
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2025)

MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets
di: Wei, Lai, et al.
Pubblicazione: (2023)

PARAMANU-GANITA: Can Small Math Language Models Rival with Large Language Models on Mathematical Reasoning?
di: Niyogi, Mitodru, et al.
Pubblicazione: (2024)

APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets
di: Liu, Zuxin, et al.
Pubblicazione: (2024)

Generator-Guided Crowd Reaction Assessment
di: Ghosh, Sohom, et al.
Pubblicazione: (2024)

MiGrATe: Mixed-Policy GRPO for Adaptation at Test-Time
di: Phan, Peter, et al.
Pubblicazione: (2025)

MMICT: Boosting Multi-Modal Fine-Tuning with In-Context Examples
di: Chen, Tao, et al.
Pubblicazione: (2023)

Dual-Modality Multi-Stage Adversarial Safety Training: Robustifying Multimodal Web Agents Against Cross-Modal Attacks
di: Liu, Haoyu, et al.
Pubblicazione: (2026)

Loss-to-Loss Prediction: Scaling Laws for All Datasets
di: Brandfonbrener, David, et al.
Pubblicazione: (2024)

Multi-Dimensional Behavioral Evaluation of Agentic Stock Prediction Systems Using Large Language Model Judges with Closed-Loop Reinforcement Learning Feedback
di: Ridhawi, Mohammad Al, et al.
Pubblicazione: (2026)

From Scratch to Fine-Tuned: A Comparative Study of Transformer Training Strategies for Legal Machine Translation
di: Barman, Amit, et al.
Pubblicazione: (2025)

Towards Efficient Resume Understanding: A Multi-Granularity Multi-Modal Pre-Training Approach
di: Jiang, Feihu, et al.
Pubblicazione: (2024)

MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining
di: Xiaomi, LLM-Core, et al.
Pubblicazione: (2025)

MMSR: Symbolic Regression is a Multi-Modal Information Fusion Task
di: Li, Yanjie, et al.
Pubblicazione: (2024)

TableDART: Dynamic Adaptive Multi-Modal Routing for Table Understanding
di: Xing, Xiaobo, et al.
Pubblicazione: (2025)

CausalStock: Deep End-to-end Causal Discovery for News-driven Stock Movement Prediction
di: Li, Shuqi, et al.
Pubblicazione: (2024)