Cover Image

DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhou, Zijian, Lin, Xiaoqiang, Xu, Xinyi, Prakash, Alok, Rus, Daniela, Low, Bryan Kian Hsiang
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TETRIS: Optimal Draft Token Selection for Batch Speculative Decoding
by: Wu, Zhaoxuan, et al.
Published: (2025)

MineDraft: A Framework for Batch Parallel Speculative Decoding
by: Tang, Zhenwei, et al.
Published: (2026)

Data value estimation on private gradients
by: Zhou, Zijian, et al.
Published: (2024)

MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents
by: Zhou, Zijian, et al.
Published: (2025)

REFRAG: Rethinking RAG based Decoding
by: Lin, Xiaoqiang, et al.
Published: (2025)

ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment
by: Lin, Xiaoqiang, et al.
Published: (2025)

MeMo: Memory as a Model
by: Quek, Ryan Wei Heng, et al.
Published: (2026)

Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions
by: Wang, Jingtan, et al.
Published: (2024)

ReasonIR: Training Retrievers for Reasoning Tasks
by: Shao, Rulin, et al.
Published: (2025)

Active Human Feedback Collection via Neural Contextual Dueling Bandits
by: Verma, Arun, et al.
Published: (2025)

Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs with Semantic Space
by: Chen, Zhiliang, et al.
Published: (2025)

Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars
by: Wu, Zhaoxuan, et al.
Published: (2024)

Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
by: Lin, Xiaoqiang, et al.
Published: (2023)

TRACE: TRansformer-based Attribution using Contrastive Embeddings in LLMs
by: Wang, Cheng, et al.
Published: (2024)

BarrierSteer: LLM Safety via Learning Barrier Steering
by: Tran, Thanh Q., et al.
Published: (2026)

Fine-tuning Language Models with Generative Adversarial Reward Modelling
by: Yu, Zhang Ze, et al.
Published: (2023)

Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
by: Verma, Arun, et al.
Published: (2024)

Global-to-Local Support Spectrums for Language Model Explainability
by: Agussurja, Lucas, et al.
Published: (2024)

Uncertainty Quantification for Multimodal Large Language Models with Incoherence-adjusted Semantic Volume
by: Lau, Gregory Kang Ruey, et al.
Published: (2026)

DETAIL Matters: Measuring the Impact of Prompt Specificity on Reasoning in Large Language Models
by: Kim, Olivia
Published: (2025)

Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
by: Lau, Gregory Kang Ruey, et al.
Published: (2024)

Prompt Optimization with Human Feedback
by: Lin, Xiaoqiang, et al.
Published: (2024)

Uncovering Scaling Laws for Large Language Models via Inverse Problems
by: Verma, Arun, et al.
Published: (2025)

Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
by: Sim, Rachael Hwee Ling, et al.
Published: (2026)

BoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks
by: Chew, Ruth Wan Theng, et al.
Published: (2026)

Dipper: Diversity in Prompts for Producing Large Language Model Ensembles in Reasoning tasks
by: Lau, Gregory Kang Ruey, et al.
Published: (2024)

DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks
by: Chen, Zhiliang, et al.
Published: (2025)

Paid with Models: Optimal Contract Design for Collaborative Machine Learning
by: Wang, Bingchen, et al.
Published: (2024)

Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies
by: Verma, Arun, et al.
Published: (2024)

COBRA: Contextual Bandit Algorithm for Ensuring Truthful Strategic Agents
by: Verma, Arun, et al.
Published: (2025)

Source Attribution for Large Language Model-Generated Data
by: Wang, Jingtan, et al.
Published: (2023)

DeRDaVa: Deletion-Robust Data Valuation for Machine Learning
by: Tian, Xiao, et al.
Published: (2023)

Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models
by: Zhang, Ze Yu, et al.
Published: (2024)

Self-Interested Agents in Collaborative Machine Learning: An Incentivized Adaptive Data-Centric Framework
by: Vijayan, Nithia, et al.
Published: (2024)

Provable Benefits of Task-Specific Prompts for In-context Learning
by: Chang, Xiangyu, et al.
Published: (2025)

Dependency Structure Search Bayesian Optimization for Decision Making Models
by: Rajpal, Mohit, et al.
Published: (2023)

StaICC: Standardized Evaluation for Classification Task in In-context Learning
by: Cho, Hakaze, et al.
Published: (2025)

Contrastive Attribution in the Wild: An Interpretability Analysis of LLM Failures on Realistic Benchmarks
by: Tan, Rongyuan, et al.
Published: (2026)

mdok-style at SemEval-2026 Task 9: Finetuning LLMs for Multilingual Polarization Detection
by: Macko, Dominik, et al.
Published: (2026)

Mechanism of Task-oriented Information Removal in In-context Learning
by: Cho, Hakaze, et al.
Published: (2025)