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 326–350 of 1135 papers

TitleStatusHype
Evaluating LLMs at Detecting Errors in LLM ResponsesCode1
Evaluating Large Language Models at Evaluating Instruction FollowingCode1
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic ScenariosCode1
Evaluating Correctness and Faithfulness of Instruction-Following Models for Question AnsweringCode1
Learning to Map Natural Language Instructions to Physical Quadcopter Control using Simulated FlightCode1
Large Language Models as Evaluators for Recommendation ExplanationsCode1
ChartInstruct: Instruction Tuning for Chart Comprehension and ReasoningCode1
LASeR: Learning to Adaptively Select Reward Models with Multi-Armed BanditsCode1
DocLens: Multi-aspect Fine-grained Evaluation for Medical Text GenerationCode1
Enhancing Cross-Tokenizer Knowledge Distillation with Contextual Dynamical MappingCode1
AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source DataCode1
CB2: Collaborative Natural Language Interaction Research PlatformCode1
LIONs: An Empirically Optimized Approach to Align Language ModelsCode1
Engineering flexible machine learning systems by traversing functionally-invariant pathsCode1
LoGU: Long-form Generation with Uncertainty ExpressionsCode1
Are Emergent Abilities in Large Language Models just In-Context Learning?Code1
Kun: Answer Polishment for Chinese Self-Alignment with Instruction Back-TranslationCode1
Lana: A Language-Capable Navigator for Instruction Following and GenerationCode1
Jatmo: Prompt Injection Defense by Task-Specific FinetuningCode1
MergeBench: A Benchmark for Merging Domain-Specialized LLMsCode1
Finding Blind Spots in Evaluator LLMs with Interpretable ChecklistsCode1
A Survey on Data Selection for LLM Instruction TuningCode1
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction TuningCode1
KaSA: Knowledge-Aware Singular-Value Adaptation of Large Language ModelsCode1
Following High-level Navigation Instructions on a Simulated Quadcopter with Imitation LearningCode1
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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