RankLLM

RankLLM

Castorini
FutureHouse RankLLM

Related Products

  • Lockbox LIMS
    4.8 out of 5 stars 72 Ratings
    Visit Website for Lockbox LIMS
  • LM-Kit.NET
    4.8 out of 5 stars 29 Ratings
    Visit Website for LM-Kit.NET
  • QBench
    4.6 out of 5 stars 153 Ratings
    Visit Website for QBench
  • Qualio
    4.4 out of 5 stars 919 Ratings
    Visit Website for Qualio
  • IONOS Cloud GPU Servers
    4.6 out of 5 stars 45,816 Ratings
    Visit Website for IONOS Cloud GPU Servers
  • Jobma
    4.6 out of 5 stars 280 Ratings
    Visit Website for Jobma
  • Pensero
    5.0 out of 5 stars 3 Ratings
    Visit Website for Pensero
  • SearchUnify
    4.5 out of 5 stars 150 Ratings
    Visit Website for SearchUnify
  • Dialpad Support
    4.4 out of 5 stars 1,629 Ratings
    Visit Website for Dialpad Support
  • CTM
    4.5 out of 5 stars 939 Ratings
    Visit Website for CTM
FutureHouse:

About

FutureHouse is a nonprofit AI research lab focused on automating scientific discovery in biology and other complex sciences. FutureHouse features superintelligent AI agents designed to assist scientists in accelerating research processes. It is optimized for retrieving and summarizing information from scientific literature, achieving state-of-the-art performance on benchmarks like RAG-QA Arena's science benchmark. It employs an agentic approach, allowing for iterative query expansion, LLM re-ranking, contextual summarization, and document citation traversal to enhance retrieval accuracy. FutureHouse also offers a framework for training language agents on challenging scientific tasks, enabling agents to perform tasks such as protein engineering, literature summarization, and molecular cloning. Their LAB-Bench benchmark evaluates language models on biology research tasks, including information extraction, database retrieval, etc.
RankLLM:

About

RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking. It offers a suite of rerankers, pointwise models like MonoT5, pairwise models like DuoT5, and listwise models compatible with vLLM, SGLang, or TensorRT-LLM. Additionally, it supports RankGPT and RankGemini variants, which are proprietary listwise rerankers. It includes modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. RankLLM integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts (MoE) models. The toolkit supports various backends, including SGLang and TensorRT-LLM, and is compatible with a wide range of LLMs.
FutureHouse:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
RankLLM:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
FutureHouse:

Audience

Academic researchers and scientists in need of a solution to enhance and accelerate their scientific discovery processes
RankLLM:

Audience

Academic researchers and developers seeking a solution offering tools for implementing and evaluating listwise reranking with large language models
FutureHouse:

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported
RankLLM:

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported
FutureHouse:

API

Offers API Not Supported
RankLLM:

API

Offers API Supported
FutureHouse:

Screenshots and Videos

RankLLM:

Screenshots and Videos

FutureHouse:

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported
RankLLM:

Pricing

Free
Free Version Supported
Free Trial Not Supported
FutureHouse:

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software
RankLLM:

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software
FutureHouse:

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Supported
RankLLM:

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported
FutureHouse:

Company Information

FutureHouse
Founded: 2023
United States
www.futurehouse.org
RankLLM:

Company Information

Castorini
Canada
github.com/castorini/rank_llm/
FutureHouse:

Alternatives

Claude Science

Claude Science

Anthropic
RankLLM:

Alternatives

RankGPT

RankGPT

Weiwei Sun
FutureHouse:
RankLLM:
ColBERT

ColBERT

Future Data Systems
FutureHouse:
Mira

Mira

Deep Principle
RankLLM:
FutureHouse:
RankLLM:
FutureHouse:
RankLLM:
FutureHouse:

Categories

Agentic AI Supported
AI Agents Supported
AI Research Tools Supported
AI Science Supported
Life Sciences Supported
RankLLM:

Categories

Reranking Models Supported
FutureHouse:

Integrations

Gemini Not Supported
Gemini Enterprise Not Supported
Llama Not Supported
Mistral AI Not Supported
NVIDIA TensorRT Not Supported
OpenAI Not Supported
Python Not Supported
Qwen Not Supported
RankGPT Not Supported
RankLLM:

Integrations

Gemini Supported
Gemini Enterprise Supported
Llama Supported
Mistral AI Supported
NVIDIA TensorRT Supported
OpenAI Supported
Python Supported
Qwen Supported
RankGPT Supported
FutureHouse:
Claim FutureHouse and update features and information
Claim FutureHouse and update features and information
RankLLM:
Claim RankLLM and update features and information
Claim RankLLM and update features and information