SOTAVerified

Instruction Following

Instruction following is the basic task of the model. This task is dedicated to evaluating the ability of the large model to follow human instructions. It is hoped that the model can generate controllable and safe answers.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 841–850 of 1135 papers

TitleStatusHype
Biomedical Visual Instruction Tuning with Clinician Preference AlignmentCode0
The Comparative Trap: Pairwise Comparisons Amplifies Biased Preferences of LLM Evaluators—0
Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal TransportCode0
Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Models—0
Refine Large Language Model Fine-tuning via Instruction Vector—0
Embodied Instruction Following in Unknown Environments—0
Enhancing and Assessing Instruction-Following with Fine-Grained Instruction Variants—0
How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment—0
Generative Visual Instruction TuningCode0
Grade Score: Quantifying LLM Performance in Option SelectionCode0
Show:102550
← PrevPage 85 of 114Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoIF (Llama3 70B)Inst-level loose-accuracy90.4—Unverified
2AutoIF (Qwen2 72B)Inst-level loose-accuracy88—Unverified
3GPT-4Inst-level loose-accuracy85.37—Unverified
4PaLM 2 SInst-level loose-accuracy59.11—Unverified