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 926–950 of 1135 papers

TitleStatusHype
Mitigating Dialogue Hallucination for Large Vision Language Models via Adversarial Instruction Tuning—0
DiffChat: Learning to Chat with Text-to-Image Synthesis Models for Interactive Image Creation—0
CoTBal: Comprehensive Task Balancing for Multi-Task Visual Instruction Tuning—0
Aligners: Decoupling LLMs and AlignmentCode0
KIWI: A Dataset of Knowledge-Intensive Writing Instructions for Answering Research Questions—0
X-Shot: A Unified System to Handle Frequent, Few-shot and Zero-shot Learning Simultaneously in ClassificationCode0
CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following—0
OPEx: A Component-Wise Analysis of LLM-Centric Agents in Embodied Instruction Following—0
Collaborative decoding of critical tokens for boosting factuality of large language models—0
Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding—0
NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation—0
Towards Robust Instruction Tuning on Multimodal Large Language ModelsCode0
Zero-shot cross-lingual transfer in instruction tuning of large language models—0
Unintended Impacts of LLM Alignment on Global RepresentationCode0
Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking—0
RefuteBench: Evaluating Refuting Instruction-Following for Large Language ModelsCode0
VL-Trojan: Multimodal Instruction Backdoor Attacks against Autoregressive Visual Language Models—0
Investigating Multilingual Instruction-Tuning: Do Polyglot Models Demand for Multilingual Instructions?—0
CIF-Bench: A Chinese Instruction-Following Benchmark for Evaluating the Generalizability of Large Language Models—0
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models—0
The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional AnalysisCode0
Transformer-based Causal Language Models Perform Clustering—0
Aligning Large Language Models by On-Policy Self-JudgmentCode0
AbsInstruct: Eliciting Abstraction Ability from LLMs through Explanation Tuning with Plausibility EstimationCode0
Efficient Prompt Optimization Through the Lens of Best Arm Identification—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