Nicky
NickyNicky
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Exciting Research Alert: Revolutionizing Complex Information Retrieval!
A groundbreaking paper from researchers at MIT, AWS AI, and UPenn introduces ARM (Alignment-Oriented LLM-based Retrieval Method), a novel approach to tackle complex information retrieval challenges.
>> Key Innovations
Information Alignment
The method first decomposes queries into keywords and aligns them with available data using both BM25 and embedding similarity, ensuring comprehensive coverage of information needs.
Structure Alignment
ARM employs a sophisticated mixed-integer programming solver to identify connections between data objects, exploring relationships beyond simple semantic matching.
Self-Verification
The system includes a unique self-verification mechanism where the LLM evaluates and aggregates results from multiple retrieval paths, ensuring accuracy and completeness.
>> Performance Highlights
The results are impressive:
- Outperforms standard RAG by up to 5.2 points in execution accuracy on Bird dataset
- Achieves 19.3 points higher F1 scores compared to existing approaches on OTT-QA
- Reduces the number of required LLM calls while maintaining superior retrieval quality
>> Technical Implementation
The system uses a three-step process:
1. N-gram indexing and embedding computation for all data objects
2. Constrained beam decoding for information alignment
3. Mixed-integer programming optimization for structure exploration
This research represents a significant step forward in making complex information retrieval more efficient and accurate. The team's work demonstrates how combining traditional optimization techniques with modern LLM capabilities can solve challenging retrieval problems.
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NickyNicky's activity
Thank you very much for this model, I have questions
1
#1 opened 6 days ago
by
NickyNicky
wow model, thank
#6 opened 6 days ago
by
NickyNicky
how to fine tune?
#10 opened 7 days ago
by
NickyNicky
model RM how?
#2 opened 11 days ago
by
NickyNicky
Librarian Bot: Add language metadata for dataset
#2 opened 17 days ago
by
librarian-bot
What advantage does this have over normal algorithmic ways of turning HTML to Markdown ?
5
#5 opened 18 days ago
by
MohamedRashad
great gift from the wise men
#1 opened 28 days ago
by
NickyNicky
example use colab?
8
#3 opened about 1 month ago
by
NickyNicky
ONNX usage
10
#14 opened about 1 month ago
by
hexgrad
notebook Colab
1
#3 opened 2 months ago
by
NickyNicky
error load model
2
#3 opened 3 months ago
by
NickyNicky
dataset generated by this model
#3 opened 3 months ago
by
NickyNicky
Thank you very much for this model, I have questions.
1
#1 opened 7 months ago
by
NickyNicky
Thanks for the models and data, I have some questions.
5
#2 opened 8 months ago
by
NickyNicky
hola, gracias por el dataset.
#1 opened 8 months ago
by
NickyNicky
Great model !!!
3
#1 opened 8 months ago
by
NickyNicky
model multi-turn?
10
#1 opened 8 months ago
by
NickyNicky
model multi-turn?
3
#2 opened 8 months ago
by
NickyNicky
Any Comfy workflow ?
6
#1 opened 8 months ago
by
3blackbar