Natural Language Processing

McKinsey's AI Lie Explains What's Happening to Work

Everyone thinks McKinsey just built 25,000 AI experts. They didn't. They took a 35-year-old internal database, put a natural language int...

Midjourney has a new offer on the cancel page there is 20 off for 2 months

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

[2510.02348] mini-vec2vec: Scaling Universal Geometry Alignment with Linear Transformations

The paper introduces mini-vec2vec, an efficient method for aligning text embedding spaces using linear transformations, significantly imp...

[2602.15772] Understanding vs. Generation: Navigating Optimization Dilemma in Multimodal Models

This paper explores the optimization dilemma in multimodal models, where enhancing generative capabilities often compromises understandin...

[2602.15758] ChartEditBench: Evaluating Grounded Multi-Turn Chart Editing in Multimodal Language Models

The paper presents ChartEditBench, a benchmark for evaluating multi-turn chart editing in multimodal language models, highlighting challe...

[2602.15757] Beyond Binary Classification: Detecting Fine-Grained Sexism in Social Media Videos

The paper presents FineMuSe, a new dataset for detecting nuanced sexism in social media videos, addressing the limitations of binary clas...

[2602.15678] Revisiting Northrop Frye's Four Myths Theory with Large Language Models

This paper explores Northrop Frye's Four Myths Theory through the lens of Large Language Models (LLMs), proposing a character function fr...

[2505.05736] Multimodal Integrated Knowledge Transfer to Large Language Models through Preference Optimization with Biomedical Applications

The paper introduces MINT, a framework for optimizing large language models (LLMs) using multimodal biomedical data to enhance predictive...

[2602.15600] The geometry of online conversations and the causal antecedents of conflictual discourse

This article explores the dynamics of conflictual discourse in online conversations, particularly focusing on climate change discussions....

[2602.15564] Beyond Static Pipelines: Learning Dynamic Workflows for Text-to-SQL

The paper presents a novel approach to Text-to-SQL systems by introducing dynamic workflows that adapt during inference, enhancing perfor...

[2602.11618] How Well Do Large-Scale Chemical Language Models Transfer to Downstream Tasks?

This paper evaluates the effectiveness of large-scale Chemical Language Models (CLMs) in transferring knowledge to downstream molecular p...

[2602.15513] Improving MLLMs in Embodied Exploration and Question Answering with Human-Inspired Memory Modeling

This paper presents a novel non-parametric memory framework for improving Multimodal Large Language Models (MLLMs) in embodied exploratio...

[2602.15491] The Equalizer: Introducing Shape-Gain Decomposition in Neural Audio Codecs

The paper presents Shape-Gain Decomposition for Neural Audio Codecs, enhancing bitrate-distortion performance and reducing complexity by ...

[2602.15397] ActionCodec: What Makes for Good Action Tokenizers

The paper introduces ActionCodec, a novel action tokenizer designed to enhance Vision-Language-Action (VLA) models by optimizing tokeniza...

[2602.15377] Orchestration-Free Customer Service Automation: A Privacy-Preserving and Flowchart-Guided Framework

This paper presents an orchestration-free framework for customer service automation, utilizing Task-Oriented Flowcharts (TOFs) to enhance...

[2602.15373] Far Out: Evaluating Language Models on Slang in Australian and Indian English

This paper evaluates the performance of language models on slang in Australian and Indian English, revealing significant gaps in understa...

[2512.19057] Efficient Personalization of Generative Models via Optimal Experimental Design

This paper presents a novel method for efficiently personalizing generative models using optimal experimental design to select preference...

[2602.15362] Automated Multi-Source Debugging and Natural Language Error Explanation for Dashboard Applications

This paper presents a novel system for Automated Multi-Source Debugging and Natural Language Error Explanation, aimed at improving user e...

[2602.15353] NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering

The paper presents NeuroSymActive, a novel framework for Knowledge Graph Question Answering that integrates differentiable neural-symboli...

[2602.15339] Benchmarking Self-Supervised Models for Cardiac Ultrasound View Classification

This article evaluates self-supervised learning models for cardiac ultrasound view classification, comparing USF-MAE and MoCo v3 using th...

[2510.02625] TabImpute: Universal Zero-Shot Imputation for Tabular Data

The paper presents TabImpute, a pre-trained transformer model designed for zero-shot imputation of missing data in tabular formats, signi...

[2507.01761] Enhanced Generative Model Evaluation with Clipped Density and Coverage

This article presents novel metrics, Clipped Density and Clipped Coverage, aimed at improving the evaluation of generative models by enha...