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 876–900 of 1135 papers

TitleStatusHype
Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checking—0
SpeechVerse: A Large-scale Generalizable Audio Language Model—0
Evaluating Robustness of Large Audio Language Models to Audio Injection: An Empirical Study—0
Evaluating the Robustness to Instructions of Large Language Models—0
Evaluation of Instruction-Following Ability for Large Language Models on Story-Ending Generation—0
Evolutionary Contrastive Distillation for Language Model Alignment—0
Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation—0
SSP: A Simple and Safe automatic Prompt engineering method towards realistic image synthesis on LVM—0
EXAONE 3.0 7.8B Instruction Tuned Language Model—0
EXAONE 3.5: Series of Large Language Models for Real-world Use Cases—0
Exo2Ego: Exocentric Knowledge Guided MLLM for Egocentric Video Understanding—0
Do we Really Need Visual Instructions? Towards Visual Instruction-Free Fine-tuning for Large Vision-Language Models—0
Explicit Object Relation Alignment for Vision and Language Navigation—0
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks—0
Exploring the Integration of Large Language Models into Automatic Speech Recognition Systems: An Empirical Study—0
Look Before You Decide: Prompting Active Deduction of MLLMs for Assumptive Reasoning—0
FaceGPT: Self-supervised Learning to Chat about 3D Human Faces—0
Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation—0
FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checking—0
AlignFormer: Modality Matching Can Achieve Better Zero-shot Instruction-Following Speech-LLM—0
Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs—0
Zero-shot cross-lingual transfer in instruction tuning of large language models—0
Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning—0
StressPrompt: Does Stress Impact Large Language Models and Human Performance Similarly?—0
Stronger Models are NOT Stronger Teachers for Instruction Tuning—0
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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