语言大模型 / LLM

Probing-RAG: Self-Probing to Guide Language Models in Selective Document Retrieval

Ingeol Baek, Hwan Chang, Byeongjeong Kim, Jimin Lee, Hwanhee Lee

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.CL

Comments NAACL 2025 Findings

Intent Tagging: Exploring Micro-Prompting Interactions for Supporting Granular Human-GenAI Co-Creation Workflows

Frederic Gmeiner, Nicolai Marquardt, Michael Bentley, Hugo Romat, Michel Pahud, David Brown, Asta Roseway, Nikolas Martelaro, Kenneth Holstein, Ken Hinckley, Nathalie Riche

专题命中 知识编辑与模型理解 ：prompting(title,abstract)；分类 cs.AI

Comments 31 pages, 30 figures, 3 tables. To appear in the Proceedings of the 2025 ACM CHI Conference on Human Factors in Computing Systems, Yokohama, Japan

Linguistically Grounded Analysis of Language Models using Shapley Head Values

Marcell Fekete, Johannes Bjerva

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.CL

Representation Engineering for Large-Language Models: Survey and Research Challenges

Lukasz Bartoszcze, Sarthak Munshi, Bryan Sukidi, Jennifer Yen, Zejia Yang, David Williams-King, Linh Le, Kosi Asuzu, Carsten Maple

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.AI

Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data

Yucheng Shi, Quanzheng Li, Jin Sun, Xiang Li, Ninghao Liu

专题命中 知识编辑与模型理解 ：foundation model(title)；language model(abstract)；分类 cs.LG

Comments Accepted by ICLR 2025. Code: https://github.com/sycny/SelfSynthX

Re-Simulation-based Self-Supervised Learning for Pre-Training Foundation Models

Philip Harris, Michael Kagan, Jeffrey Krupa, Benedikt Maier, Nathaniel Woodward

专题命中 知识编辑与模型理解 ：foundation model(title,abstract)；分类 cs.LG

Comments 14 pages, 8 figures

Journal ref Phys. Rev. D 111 (2025) 3, 032010

How do Multimodal Foundation Models Encode Text and Speech? An Analysis of Cross-Lingual and Cross-Modal Representations

Hyunji Lee, Danni Liu, Supriti Sinhamahapatra, Jan Niehues

专题命中 知识编辑与模型理解 ：foundation model(title,abstract)；分类 cs.CL

Comments NAACL 2025

Ethereum Fraud Detection via Joint Transaction Language Model and Graph Representation Learning

Jianguo Sun, Yifan Jia, Yanbin Wang, Yiwei Liu, Zhang Sheng, Ye Tian

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.LG

Artworks Reimagined: Exploring Human-AI Co-Creation through Body Prompting

Jonas Oppenlaender, Hannah Johnston, Johanna Silvennoinen, Helena Barranha

专题命中 知识编辑与模型理解 ：prompting(title,abstract)；分类 cs.AI

Comments 29 pages, 5 figures, 2 tables

AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting

Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl

专题命中 知识编辑与模型理解 ：foundation model(title,abstract)；分类 cs.LG

Interpreting and Steering Protein Language Models through Sparse Autoencoders

Edith Natalia Villegas Garcia, Alessio Ansuini

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.LG

Comments 11 pages, 6 figures

SPeCtrum: A Grounded Framework for Multidimensional Identity Representation in LLM-Based Agent

Keyeun Lee, Seo Hyeong Kim, Seolhee Lee, Jinsu Eun, Yena Ko, Hayeon Jeon, Esther Hehsun Kim, Seonghye Cho, Soeun Yang, Eun-mee Kim, Hajin Lim

专题命中 知识编辑与模型理解 ：LLM(title,abstract)；分类 cs.CL

Comments 21 pages, 8 figures, 5 tables, Accepted in NAACL2025 Main

Obfuscated Activations Bypass LLM Latent-Space Defenses

Luke Bailey, Alex Serrano, Abhay Sheshadri, Mikhail Seleznyov, Jordan Taylor, Erik Jenner, Jacob Hilton, Stephen Casper, Carlos Guestrin, Scott Emmons

专题命中 知识编辑与模型理解 ：LLM(title,abstract)；分类 cs.LG

Comments Project page: https://obfuscated-activations.github.io/ Code: https://github.com/LukeBailey181/obfuscated-activations

A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation

Bairu Hou, Yang Zhang, Jacob Andreas, Shiyu Chang

专题命中 知识编辑与模型理解 ：LLM(title,abstract)；分类 cs.CL

Comments NAACL 2025 (main conference)

When One LLM Drools, Multi-LLM Collaboration Rules

Shangbin Feng, Wenxuan Ding, Alisa Liu, Zifeng Wang, Weijia Shi, Yike Wang, Zejiang Shen, Xiaochuang Han, Hunter Lang, Chen-Yu Lee, Tomas Pfister, Yejin Choi, Yulia Tsvetkov

专题命中 知识编辑与模型理解 ：LLM(title,abstract)；分类 cs.CL

Color in Visual-Language Models: CLIP deficiencies

Guillem Arias, Ramon Baldrich, Maria Vanrell

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.AI

Comments 6 pages, 10 figures, conference, Artificial Intelligence

Journal ref in Color and Imaging Conference, 2024, pp 101 - 106

Multi-megabase scale genome interpretation with genetic language models

Frederik Träuble, Lachlan Stuart, Andreas Georgiou, Pascal Notin, Arash Mehrjou, Ron Schwessinger, Mathieu Chevalley, Kim Branson, Bernhard Schölkopf, Cornelia van Duijn, Debora Marks, Patrick Schwab

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.LG

Linguistic Entity Masking to Improve Cross-Lingual Representation of Multilingual Language Models for Low-Resource Languages

Aloka Fernando, Surangika Ranathunga

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.CL

Generative power of a protein language model trained on multiple sequence alignments

Damiano Sgarbossa, Umberto Lupo, Anne-Florence Bitbol

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.LG

Comments 46 pages, 20 figures, 6 tables

Journal ref eLife 12: e79854 (2023)

Montague semantics and modifier consistency measurement in neural language models

Danilo S. Carvalho, Edoardo Manino, Julia Rozanova, Lucas Cordeiro, André Freitas

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.CL

RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models

Sangmin Woo, Jaehyuk Jang, Donguk Kim, Yubin Choi, Changick Kim

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.AI

Comments Project: https://sangminwoo.github.io/RITUAL/

Language model driven: a PROTAC generation pipeline with dual constraints of structure and property

Jinsong Shao, Qineng Gong, Zeyu Yin, Yu Chen, Yajie Hao, Lei Zhang, Linlin Jiang, Min Yao, Jinlong Li, Fubo Wang, Li Wang

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.AI

Comments 61 pages,12 figures

Concept Bottleneck Language Models For protein design

Aya Abdelsalam Ismail, Tuomas Oikarinen, Amy Wang, Julius Adebayo, Samuel Stanton, Taylor Joren, Joseph Kleinhenz, Allen Goodman, Héctor Corrada Bravo, Kyunghyun Cho, Nathan C. Frey

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.LG

Multimodal Fact-Checking with Vision Language Models: A Probing Classifier based Solution with Embedding Strategies

Recep Firat Cekinel, Pinar Karagoz, Cagri Coltekin

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.CL

Comments Accepted to COLING2025

Exploring Aleatoric Uncertainty in Object Detection via Vision Foundation Models

Peng Cui, Guande He, Dan Zhang, Zhijie Deng, Yinpeng Dong, Jun Zhu

专题命中 知识编辑与模型理解 ：foundation model(title,abstract)；分类 cs.LG

Finding Structure in Language Models

Jaap Jumelet

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.CL

Comments PhD Thesis at ILLC, University of Amsterdam

DoubleCCA: Improving Foundation Model Group Robustness with Random Sentence Embeddings

Hong Liu, Yitong Lu

专题命中 知识编辑与模型理解 ：foundation model(title,abstract)；分类 cs.CL

Comments 18 pages, 6 figures, 2 tables

ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Junzhe Chen, Tianshu Zhang, Shiyu Huang, Yuwei Niu, Linfeng Zhang, Lijie Wen, Xuming Hu

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.CL

Enhancing Language Model Factuality via Activation-Based Confidence Calibration and Guided Decoding

Xin Liu, Farima Fatahi Bayat, Lu Wang

专题命中 知识编辑与模型理解 ：language model(title,abstract)；分类 cs.CL

Comments EMNLP 2024 Camera Ready

DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features

Letian Wang, Seung Wook Kim, Jiawei Yang, Cunjun Yu, Boris Ivanovic, Steven L. Waslander, Yue Wang, Sanja Fidler, Marco Pavone, Peter Karkus

专题命中 知识编辑与模型理解 ：foundation model(title,abstract)；分类 cs.AI

Comments Accepted by Advances in Neural Information Processing Systems (NeurIPS 2024)