OpenAI
GPT-3.5 Turbo
Instruction-tuned · 2023-03-01 · Verified
Research summary
Research summary
Model positioningGeneralReasoning
Access and distribution ladder
ProductPending verificationPending verification
APIYesavailable
WeightsNoNo
BaseNoNo
Finetuning allowedNoNo
Derivative distributionNoNo
At a glance
Unresolved fields
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9 key fields need verification
How to read unknown states
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- The official source does not disclose this; do not infer that it is absent.
- Not applicableThis field does not apply to this record; it is not missing or negative.
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- Not reportedThe source or paper did not report it; this is not false, zero, or confirmed absence.
- The source or paper did not report it; this is not false, zero, or confirmed absence.
- Not verifiedThe field is retained, but current evidence is not verified; add first-party evidence before relying on it.
- The field is retained, but current evidence is not verified; add first-party evidence before relying on it.
- Conflicting evidenceFirst-party sources conflict; no single value is selected.
- First-party sources conflict; no single value is selected.
- Not publishedThe record is not published yet; this is not the same as a broken source link.
- The record is not published yet; this is not the same as a broken source link.
- UnavailableThe current source is unavailable; do not infer that the fact does not exist.
- The current source is unavailable; do not infer that the fact does not exist.
Access & distribution
Specializations & research readiness
GeneralReasoning
Hardware tiers
Paper adoption
AgentBench: Evaluating LLMs as Agents
Baseline
AgentBoard: An Analytical Evaluation Board of LLM Agents
Baseline
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
Actor
CAMEL: Communicative Agents for Mind Exploration of Large Scale Language Model Society
Actor
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models
Actor
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Policy
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Policy
ExpeL: LLM Agents Are Experiential Learners
Reflector
Generative Agents: Interactive Simulacra of Human Behavior
Policy
Self-Refine: Iterative Refinement with Self-Feedback
Policy
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
Baseline
WebArena: A Realistic Web Environment for Building Autonomous Agents
Baseline
Replacement candidates and family versions
Candidates are derived from catalog family, generation, and release metadata; this is not a quality score or a substitute for experiments.