Natural Language Processing

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Walmart CEO reportedly brags that company's in-app AI agent is making people spend 35% more money

[R] Looking for arXiv cs.LG endorser, inference monitoring using information geometry

Hi r/MachineLearning, I’m looking for an arXiv endorser in cs.LG for a paper on inference-time distribution shift detection for deployed ...

[2602.15852] Building Safe and Deployable Clinical Natural Language Processing under Temporal Leakage Constraints

This article discusses the development of clinical NLP models that mitigate risks associated with temporal leakage, emphasizing the impor...

[2602.15851] Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Survey

This survey explores the intersection of narrative theory and large language models (LLMs) for automatic story generation and understandi...

[2602.15849] Preference Optimization for Review Question Generation Improves Writing Quality

This article presents IntelliReward, a novel model for generating review questions that enhances writing quality by aligning with human p...

[2602.16436] Learning with Locally Private Examples by Inverse Weierstrass Private Stochastic Gradient Descent

This paper presents a novel method for correcting bias in binary classification tasks using locally private examples, leveraging the Inve...

[2602.15848] Can LLMs Assess Personality? Validating Conversational AI for Trait Profiling

This study evaluates the effectiveness of Large Language Models (LLMs) in assessing personality traits compared to traditional questionna...

[2602.15844] Language Model Representations for Efficient Few-Shot Tabular Classification

This paper explores the use of language model representations for efficient few-shot classification of tabular data, proposing a new para...

[2602.16578] Creating a digital poet

This paper explores the creation of a digital poet using a large language model, detailing a workshop where the model developed a unique ...

[2602.16316] A Graph Meta-Network for Learning on Kolmogorov-Arnold Networks

This paper introduces WS-KAN, a novel weight-space architecture for Kolmogorov-Arnold Networks (KANs), demonstrating its superior perform...

[2602.16284] Fast KV Compaction via Attention Matching

The paper presents a novel approach for fast key-value (KV) compaction via Attention Matching, addressing the challenges of scaling langu...

[2602.16481] Leveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach

This article explores the use of large language models (LLMs) in causal discovery, proposing a constraint-based, argumentation-driven app...

[2602.16424] Verifiable Semantics for Agent-to-Agent Communication

This paper introduces a certification protocol for agent-to-agent communication in multiagent AI systems, addressing semantic drift and e...

[2602.16192] Revolutionizing Long-Term Memory in AI: New Horizons with High-Capacity and High-Speed Storage

This article discusses innovative approaches to long-term memory in AI, emphasizing the importance of retaining raw experiences for bette...

[2602.16066] Improving Interactive In-Context Learning from Natural Language Feedback

This paper presents a novel framework for improving interactive in-context learning in large language models by utilizing natural languag...

[2602.16169] Discrete Stochastic Localization for Non-autoregressive Generation

The paper presents Discrete Stochastic Localization (DSL), a method that enhances non-autoregressive generation by improving the efficien...

[2602.16101] Axle Sensor Fusion for Online Continual Wheel Fault Detection in Wayside Railway Monitoring

This paper presents a novel framework for online continual wheel fault detection in railway systems using axle sensor fusion and machine ...

[2602.16092] Why Any-Order Autoregressive Models Need Two-Stream Attention: A Structural-Semantic Tradeoff

The paper explores the necessity of two-stream attention in any-order autoregressive models, highlighting a structural-semantic tradeoff ...

[2602.16015] Geometry-Aware Uncertainty Quantification via Conformal Prediction on Manifolds

This paper introduces adaptive geodesic conformal prediction, a novel framework for uncertainty quantification on Riemannian manifolds, e...

[2602.15961] R$^2$Energy: A Large-Scale Benchmark for Robust Renewable Energy Forecasting under Diverse and Extreme Conditions

The paper presents R$^2$Energy, a benchmark for robust renewable energy forecasting, addressing challenges posed by extreme weather and g...

[2602.15842] Memes-as-Replies: Can Models Select Humorous Manga Panel Responses?

This article explores the Meme Reply Selection task, analyzing how large language models (LLMs) can select humorous manga panel responses...

[P] Utterance, an open source client-side semantic endpointing SDK for voice apps. We are looking for contributors.

Utterance is an open-source SDK designed to improve voice app interactions by addressing issues with pauses and interruptions, inviting c...