[D] ICML 26 - What to do with the zero follow-up questions
Hello everyone. I submitted my work to ICML 26 this year, and it got somewhat above average reviews. Now, in the rebuttal acknowledgment,...
Text understanding and language tasks
Hello everyone. I submitted my work to ICML 26 this year, and it got somewhat above average reviews. Now, in the rebuttal acknowledgment,...
Nominate your startup, or one you know, and apply for a chance at VC access, TechCrunch coverage, and $100K for Startup Battlefield 200.
Abstract page for arXiv paper 2603.24326: Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing
The paper discusses how introspective experiences from conversational environments can enhance learning in AI systems, arguing for the im...
The ROAST technique enhances the control of large language models by utilizing on-distribution rollouts for more effective activation ste...
The paper introduces Concept Influence, a method to enhance training data attribution by leveraging interpretability, improving performan...
The paper presents EmbeWebAgent, a framework for embedding web agents into existing user interfaces, enhancing their robustness and actio...
This paper introduces a novel position encoding strategy, Random Float Sampling (RFS), which enhances the length generalization capabilit...
WebWorld introduces a large-scale simulator for training web agents, utilizing over 1 million open-web interactions to enhance generaliza...
The paper presents Arbor, a framework designed to enhance the navigation of critical conversation flows in high-stakes environments like ...
This paper explores an innovative approach to tokenization in large language models (LLMs) using reinforcement learning, demonstrating im...
The article presents GREPO, a benchmark for evaluating Graph Neural Networks (GNNs) in repository-level bug localization, addressing limi...
The paper introduces Precedent-Informed Reasoning (PIR) to enhance reasoning in Large Language Models (LLMs) by leveraging past cases, im...
This study explores the efficacy of reasoning traces in neural networks, introducing a large dataset to assess how well models generalize...
The paper introduces GRAIL, a method for recognizing agent goals through imitation learning, enhancing goal recognition accuracy in AI sy...
The paper presents MEMTS, a novel method for domain adaptation in time series forecasting that internalizes domain knowledge through a Kn...
The paper presents the REAL framework, which addresses knowledge conflicts in Knowledge-Intensive Visual Question Answering (KI-VQA) by i...
The paper introduces FloCA, a flowchart-oriented conversational agent designed to enhance decision-making in dialogue systems by ensuring...
This paper presents a novel framework for denoising magnetic navigation data using physics-aware neural networks, addressing challenges i...
This article presents a novel method called Parallelized Iterative Compression (PIC) for enhancing soft prompt compression in Large Langu...
The paper presents Neuromem, a framework for evaluating external memory modules in large language models (LLMs) under a dynamic streaming...
The paper presents statistical early stopping methods for reasoning models, addressing inefficiencies in large language models (LLMs) tha...
The paper presents HyMem, a hybrid memory architecture designed to enhance the performance of large language models (LLMs) in extended di...
Get the latest news, tools, and insights delivered to your inbox.
Daily or weekly digest • Unsubscribe anytime