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 901–925 of 1135 papers

TitleStatusHype
Unveiling the Misuse Potential of Base Large Language Models via In-Context Learning—0
Sketch-Plan-Generalize: Learning and Planning with Neuro-Symbolic Programmatic Representations for Inductive Spatial Concepts—0
CodecLM: Aligning Language Models with Tailored Synthetic Data—0
Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs—0
Teaching Llama a New Language Through Cross-Lingual Knowledge TransferCode0
CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues—0
An Incomplete Loop: Deductive, Inductive, and Abductive Learning in Large Language Models—0
HyperCLOVA X Technical Report—0
Token-Efficient Leverage Learning in Large Language ModelsCode0
LLaMA-Excitor: General Instruction Tuning via Indirect Feature Interaction—0
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language ReasoningCode0
CoDa: Constrained Generation based Data Augmentation for Low-Resource NLPCode0
Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks—0
Plug-and-Play Grounding of Reasoning in Multimodal Large Language Models—0
InstUPR : Instruction-based Unsupervised Passage Reranking with Large Language ModelsCode0
RL for Consistency Models: Faster Reward Guided Text-to-Image Generation—0
WangchanLion and WangchanX MRC EvalCode0
Argument Quality Assessment in the Age of Instruction-Following Large Language Models—0
Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning—0
Improving the Robustness of Large Language Models via Consistency Alignment—0
Building Accurate Translation-Tailored LLMs with Language Aware Instruction TuningCode0
VisualCritic: Making LMMs Perceive Visual Quality Like Humans—0
WoLF: Wide-scope Large Language Model Framework for CXR Understanding—0
Third-Party Language Model Performance Prediction from InstructionCode0
Don't Half-listen: Capturing Key-part Information in Continual 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