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 251–275 of 1135 papers

TitleStatusHype
Zero-Shot Compositional Policy Learning via Language GroundingCode1
LIONs: An Empirically Optimized Approach to Align Language ModelsCode1
Aya Dataset: An Open-Access Collection for Multilingual Instruction TuningCode1
Beyond Task Performance: Evaluating and Reducing the Flaws of Large Multimodal Models with In-Context LearningCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
Lexicon Learning for Few-Shot Neural Sequence ModelingCode1
Counterfactual Cycle-Consistent Learning for Instruction Following and Generation in Vision-Language NavigationCode1
Lexicon Learning for Few Shot Sequence ModelingCode1
LLaSA: A Multimodal LLM for Human Activity Analysis Through Wearable and Smartphone SensorsCode1
LASeR: Learning to Adaptively Select Reward Models with Multi-Armed BanditsCode1
Large Language Models as Evaluators for Recommendation ExplanationsCode1
CoPESD: A Multi-Level Surgical Motion Dataset for Training Large Vision-Language Models to Co-Pilot Endoscopic Submucosal DissectionCode1
CoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction TuningCode1
Contrastive Vision-Language Alignment Makes Efficient Instruction LearnerCode1
Enhancing Cross-Tokenizer Knowledge Distillation with Contextual Dynamical MappingCode1
Learning to Map Natural Language Instructions to Physical Quadcopter Control using Simulated FlightCode1
Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation ExtractorsCode1
AutoDetect: Towards a Unified Framework for Automated Weakness Detection in Large Language ModelsCode1
Language Imbalance Driven Rewarding for Multilingual Self-improvingCode1
Context-Aware Planning and Environment-Aware Memory for Instruction Following Embodied AgentsCode1
Constraint Back-translation Improves Complex Instruction Following of Large Language ModelsCode1
Lana: A Language-Capable Navigator for Instruction Following and GenerationCode1
Evaluating Correctness and Faithfulness of Instruction-Following Models for Question AnsweringCode1
Engineering flexible machine learning systems by traversing functionally-invariant pathsCode1
Language-Conditioned Reinforcement Learning to Solve Misunderstandings with Action CorrectionsCode1
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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