Paper page - LLMs Can Leak Training Data But Do They Want To? A Propensity-Aware Evaluation of Memorization in LLMs
Papers arxiv:2606.06286 LLMs Can Leak Training Data But Do They Want To? …
Tracked topic
Large language models are machine learning models trained to predict and generate text and other language-based outputs.
Papers arxiv:2606.06286 LLMs Can Leak Training Data But Do They Want To? …
… The following papers were recommended by the Semantic Scholar API Synthetic Contrastive Reasoning for Multi-Table Q&A 2026 Teaching Language Models to Check Grounded Claim Factuality with Human Test-Taking Strategies 2026 Hint Tuning: Less Data Makes Better Reasoners 2026 Learning More from Less: E… …
Papers arxiv:2606.31036 Teaching LLMs to Recommend and Defer in Underrepresented Epilepsy Care Published on Jun 30 Submitted by Kartik Sharma on Jul 6 University of California, Los Angeles Authors: , Kartik Sharma , , , , , , , , , Abstract A non-parametric prompt-learning framework called MANANA i… …
Papers arxiv:2605.26242 Can LLMs Introspect? …
Papers arxiv:2605.08083 LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling Published on May 8 Submitted by Chengsong Huang on May 11 3 Paper of the day Google Authors: Tong Zheng , , , , , , Runpeng Dai , , , Tianyi Xiong , , , Abstract AutoTTS automates test-time scaling strategy discove… …
… Despite this, LLMs are still predominantly evaluated or trained in single-turn, fully-specified settings, leaving open a fundamental question: how well do LLMs track and act on user intent as it evolves over the course of a conversation? …
You can also plug them into MUDs the few that still exist at least! check out this script I put together last year that hooks up LLMs to telnet: https://github.com/CharlesCNorton/Language-Model-Tools/tree/main/AutoMUD This comment has been hidden marked as Spam Former MUD player here, love this ide… …
Papers arxiv:2606.00125 Multimodal Music Recommendation System using LLMs Published on May 28 Submitted by Franck Dernoncourt on Jun 5 Authors: , , , , , , , Franck Dernoncourt , Abstract A multimodal framework for session-based music recommendation integrates audio, lyric, and semantic signals wit… …
… We run experiments across four behavioral tasks and 11 frontier LLMs , while also varying session context and identity induction. …
… We release ModSleuth and the resulting dependency graphs to support transparent analysis of the increasingly complex ecosystems underlying modern LLMs. …