Large Language Model - Tag Page 2 - DataSci Ocean

Large Language Model

2026

Why Your RAG Fails at Complex Tables—And How MixRAG Fixes It: A Deep Dive into Heterogeneous Document Retrieval 03-15

Deep Dive into MRAG: Solving Temporal Reasoning in RAG with Symbolic Logic (EMNLP 2025) 03-10

Selective Clarification: Overcoming LLM Hallucinations via the CLAM Framework 02-25

[EMNLP 2025] TableRAG Deep Dive: Text is for Reading, Tables are for Querying (via SQL) 02-13

Stop LLMs From Blindly Guessing: A Deep Dive into "Clarify When Necessary" (NAACL 2025) 02-08

Beyond HyDE: How ReDE-RF Makes RAG 10x Faster by "Judging" Instead of "Writing" 02-03

Google's "Free Lunch" for LLMs: How Prompt Repetition Fixes Attention Bottlenecks with Zero Latency 01-19

Is RLHF Killing Creativity? How Verbalized Sampling Mitigates Mode Collapse and Unlocks LLM Diversity 01-03

Beyond Self-Consistency: How CER Boosts LLM Reasoning by Leveraging "Process Confidence" (ACL 2025) 01-03

2025

Stop AI Hallucinations Early: How Meta's DeepConf Uses Token Confidence to Cut Inference Costs by 80% 12-28

rStar Deep Dive: How MCTS & Mutual Reasoning Boost LLaMA2-7B Accuracy from 12% to 64% Without Fine-tuning 12-10

Your Base Model Is Smarter Than You Think: How MCMC Sampling Can Outperform RL 12-02

Beyond Prompt Engineering: Inside Agentic Context Engineering, The Future of Self-Evolving AI 10-27

Dynamic Cheatsheet: The Secret to Self-Improving LLMs that Learn During Inference 10-15

Let AI Write Flawless SQL: A Deep Dive into the SQL-of-Thought Multi-Agent Framework 10-12

Beyond Top-k: How Adaptive-k Dynamically Selects the Best Context for RAG Without Latency 09-22

SENSE Explained: How Strong and Weak LLMs Achieve State-of-the-Art Text-to-SQL (ACL 2024) 09-15

MIRIX: Multi-Agent Memory System for LLM-Based Agents 07-17

Decoupled Planning and Execution: A Hierarchical Reasoning Framework for Deep Search 07-06

AutoMind: Adaptive Knowledgeable Agent for Automated Data Science 06-28

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