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Machine Learning

[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,...

Reddit - Machine Learning · 1 min ·
Startup Battlefield 200 applications open until May 27 | TechCrunch
Nlp

Startup Battlefield 200 applications open until May 27 | TechCrunch

Nominate your startup, or one you know, and apply for a chance at VC access, TechCrunch coverage, and $100K for Startup Battlefield 200.

TechCrunch - AI · 4 min ·
[2603.24326] Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing
Llms

[2603.24326] Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing

Abstract page for arXiv paper 2603.24326: Boosting Document Parsing Efficiency and Performance with Coarse-to-Fine Visual Processing

arXiv - AI · 4 min ·

All Content

[2602.14910] Position: Introspective Experience from Conversational Environments as a Path to Better Learning
Machine Learning

[2602.14910] Position: Introspective Experience from Conversational Environments as a Path to Better Learning

The paper discusses how introspective experiences from conversational environments can enhance learning in AI systems, arguing for the im...

arXiv - AI · 4 min ·
[2602.14143] ROAST: Rollout-based On-distribution Activation Steering Technique
Llms

[2602.14143] ROAST: Rollout-based On-distribution Activation Steering Technique

The ROAST technique enhances the control of large language models by utilizing on-distribution rollouts for more effective activation ste...

arXiv - Machine Learning · 3 min ·
[2602.14869] Concept Influence: Leveraging Interpretability to Improve Performance and Efficiency in Training Data Attribution
Llms

[2602.14869] Concept Influence: Leveraging Interpretability to Improve Performance and Efficiency in Training Data Attribution

The paper introduces Concept Influence, a method to enhance training data attribution by leveraging interpretability, improving performan...

arXiv - AI · 4 min ·
[2602.14865] EmbeWebAgent: Embedding Web Agents into Any Customized UI
Nlp

[2602.14865] EmbeWebAgent: Embedding Web Agents into Any Customized UI

The paper presents EmbeWebAgent, a framework for embedding web agents into existing user interfaces, enhancing their robustness and actio...

arXiv - AI · 3 min ·
[2602.14050] Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers
Llms

[2602.14050] Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers

This paper introduces a novel position encoding strategy, Random Float Sampling (RFS), which enhances the length generalization capabilit...

arXiv - Machine Learning · 3 min ·
[2602.14721] WebWorld: A Large-Scale World Model for Web Agent Training
Machine Learning

[2602.14721] WebWorld: A Large-Scale World Model for Web Agent Training

WebWorld introduces a large-scale simulator for training web agents, utilizing over 1 million open-web interactions to enhance generaliza...

arXiv - AI · 3 min ·
[2602.14643] Arbor: A Framework for Reliable Navigation of Critical Conversation Flows
Llms

[2602.14643] Arbor: A Framework for Reliable Navigation of Critical Conversation Flows

The paper presents Arbor, a framework designed to enhance the navigation of critical conversation flows in high-stakes environments like ...

arXiv - AI · 4 min ·
[2602.13940] You Can Learn Tokenization End-to-End with Reinforcement Learning
Llms

[2602.13940] You Can Learn Tokenization End-to-End with Reinforcement Learning

This paper explores an innovative approach to tokenization in large language models (LLMs) using reinforcement learning, demonstrating im...

arXiv - AI · 3 min ·
[2602.13921] GREPO: A Benchmark for Graph Neural Networks on Repository-Level Bug Localization
Llms

[2602.13921] GREPO: A Benchmark for Graph Neural Networks on Repository-Level Bug Localization

The article presents GREPO, a benchmark for evaluating Graph Neural Networks (GNNs) in repository-level bug localization, addressing limi...

arXiv - AI · 4 min ·
[2602.14451] Precedent-Informed Reasoning: Mitigating Overthinking in Large Reasoning Models via Test-Time Precedent Learning
Llms

[2602.14451] Precedent-Informed Reasoning: Mitigating Overthinking in Large Reasoning Models via Test-Time Precedent Learning

The paper introduces Precedent-Informed Reasoning (PIR) to enhance reasoning in Large Language Models (LLMs) by leveraging past cases, im...

arXiv - AI · 4 min ·
[2602.14404] Boule or Baguette? A Study on Task Topology, Length Generalization, and the Benefit of Reasoning Traces
Machine Learning

[2602.14404] Boule or Baguette? A Study on Task Topology, Length Generalization, and the Benefit of Reasoning Traces

This study explores the efficacy of reasoning traces in neural networks, introducing a large dataset to assess how well models generalize...

arXiv - Machine Learning · 4 min ·
[2602.14252] GRAIL: Goal Recognition Alignment through Imitation Learning
Nlp

[2602.14252] GRAIL: Goal Recognition Alignment through Imitation Learning

The paper introduces GRAIL, a method for recognizing agent goals through imitation learning, enhancing goal recognition accuracy in AI sy...

arXiv - Machine Learning · 3 min ·
[2602.13783] MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Models
Llms

[2602.13783] MEMTS: Internalizing Domain Knowledge via Parameterized Memory for Retrieval-Free Domain Adaptation of Time Series Foundation Models

The paper presents MEMTS, a novel method for domain adaptation in time series forecasting that internalizes domain knowledge through a Kn...

arXiv - Machine Learning · 4 min ·
[2602.14065] REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment
Machine Learning

[2602.14065] REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment

The paper presents the REAL framework, which addresses knowledge conflicts in Knowledge-Intensive Visual Question Answering (KI-VQA) by i...

arXiv - AI · 3 min ·
[2602.14035] FloCA: Towards Faithful and Logically Consistent Flowchart Reasoning
Llms

[2602.14035] FloCA: Towards Faithful and Logically Consistent Flowchart Reasoning

The paper introduces FloCA, a flowchart-oriented conversational agent designed to enhance decision-making in dialogue systems by ensuring...

arXiv - AI · 4 min ·
[2602.13690] Physics Aware Neural Networks: Denoising for Magnetic Navigation
Machine Learning

[2602.13690] Physics Aware Neural Networks: Denoising for Magnetic Navigation

This paper presents a novel framework for denoising magnetic navigation data using physics-aware neural networks, addressing challenges i...

arXiv - Machine Learning · 4 min ·
[2602.13980] Cognitive Chunking for Soft Prompts: Accelerating Compressor Learning via Block-wise Causal Masking
Llms

[2602.13980] Cognitive Chunking for Soft Prompts: Accelerating Compressor Learning via Block-wise Causal Masking

This article presents a novel method called Parallelized Iterative Compression (PIC) for enhancing soft prompt compression in Large Langu...

arXiv - Machine Learning · 4 min ·
[2602.13967] Neuromem: A Granular Decomposition of the Streaming Lifecycle in External Memory for LLMs
Llms

[2602.13967] Neuromem: A Granular Decomposition of the Streaming Lifecycle in External Memory for LLMs

The paper presents Neuromem, a framework for evaluating external memory modules in large language models (LLMs) under a dynamic streaming...

arXiv - AI · 4 min ·
[2602.13935] Statistical Early Stopping for Reasoning Models
Llms

[2602.13935] Statistical Early Stopping for Reasoning Models

The paper presents statistical early stopping methods for reasoning models, addressing inefficiencies in large language models (LLMs) tha...

arXiv - Machine Learning · 3 min ·
[2602.13933] HyMem: Hybrid Memory Architecture with Dynamic Retrieval Scheduling
Llms

[2602.13933] HyMem: Hybrid Memory Architecture with Dynamic Retrieval Scheduling

The paper presents HyMem, a hybrid memory architecture designed to enhance the performance of large language models (LLMs) in extended di...

arXiv - AI · 4 min ·
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