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20242026
most citedA Survey of Context Engineering for Large Language Models

13 citations · 20 across the 37 of their papers we have counts for

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27 papers · 1 filter

cs.CL2026

LP-SFT: Local-Preserving Supervised Fine-Tuning via Multimodal Entropy Structure

Yueyang Wang, Baolong Bi, Shuo Lu +2

Supervised fine-tuning (SFT) is the standard approach for adapting pretrained language models to downstream domains, yet it often improves target-domain behavior at the cost of deg…

cs.CL2026

PRISM-: Differential Subspace Steering for Prompt Highlighting in Large Language Models

Yuyao Ge, Shenghua Liu, Yiwei Wang +5

Prompt highlighting steers a large language model to prioritize user-specified text spans during generation. A key challenge of existing Key-editing approaches is extracting steeri…

cs.CL2026

Gated Differentiable Working Memory for Long-Context Language Modeling

Lingrui Mei, Shenghua Liu, Yiwei Wang +7

Long contexts challenge transformers: attention scores dilute across thousands of tokens, critical information is often lost in the middle, and models struggle to adapt to novel pa…

cs.CL2025

Not in Sync: Unveiling Temporal Bias in Audio Chat Models

Jiayu Yao, Shenghua Liu, Yiwei Wang +5

Large Audio Language Models (LALMs) are increasingly applied to audio understanding and multimodal reasoning, yet their ability to locate when events occur remains underexplored. W…

cs.CL2025

Beyond Black-Box Interventions: Latent Probing for Faithful Retrieval-Augmented Generation

Linfeng Gao, Qinggang Zhang, Baolong Bi +9

Retrieval-Augmented Generation (RAG) systems often fail to maintain contextual faithfulness, generating responses that conflict with the provided context or fail to fully leverage…

cs.CL2025

How to Make Large Language Models Generate 100% Valid Molecules?

Wen Tao, Jing Tang, Alvin Chan +5

Molecule generation is key to drug discovery and materials science, enabling the design of novel compounds with specific properties. Large language models (LLMs) can learn to perfo…