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Nlp coverage.

Every story in the WeSearch catalog tagged with #nlp, chronological, with view counts. Subscribe to the per-tag RSS feed to follow this topic in your reader of choice.

17 stories tagged with #nlp, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.

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#ai6#python4#llm2#opensource2#github2#technology2#ml2#gemma1#arabic-nlp1#productivity1#automation1#luis-faria1
DEV.TO (TOP)

I spent a week on regex before realizing AI agent was the answer for data extraction

I spent a week on regex before realizing AI agent was the answer for data extraction A couple of...…

15 views ·
#ai#data extraction
DEV.TO (TOP)

How I Built a 7-Layer NL2SQL Guardrail Stack for a Fortune 500 Enterprise

Liquid syntax error: Unknown tag 'endraw'…

22 views ·
#aisafety#nl2sql
KDNUGGETS

Practical NLP in the Browser with Transformers.js

This tutorial covers three NLP tasks: text classification, zero-shot labelling, and question answering using Transformers.js's pipeline() API.…

23 views ·
#javascript#transformers
TRELK

Show HN: Trelk – Read, Think, Connect

Your personal knowledge base. Save articles, papers, and notes. AI connects your ideas.…

13 views ·
#ai#technology
DEV.TO (TOP)

Dual Encoder vs Cross-Encoder: Why Your RAG Pipeline Needs Both

My RAG pipeline looked fine on paper. Fast retrieval. Decent cosine scores. But when I tested it with...…

16 views ·
#machine learning#retrieval
ARXIV CS.AI

LELA: An End-to-end LLM-based Entity Linking Framework with Zero-shot Domain Adaptation

Entity linking is a key component of many downstream NLP systems, yet existing approaches are often tied to the specific target knowledge bases and domains, limiting their real wor…

14 views ·
#artificial intelligence#entity linking
R/MACHINELEARNING

Already 11 000 submissions for EMNLP? [D]

19 views ·
ARXIV CS.AI

Uncertainty Decomposition via Cyclical SG-MCMC and Soft-label Learning for Subjective NLP

Annotator disagreement in emotion classification reflects ambiguity intrinsic to emotion concepts and is essential for predictor-quality assessment in subjective NLP. Yet no prior …

16 views ·
#artificial intelligence#machine learning
DEV.TO (TOP)

I Built a Multilingual Spam Detection Dataset with 149K+ Messages Across 23 Languages

Spam detection datasets are surprisingly bad once you move outside English. Most public datasets...…

17 views ·
#spam#dataset
ARXIV CS.AI

DreamerNLplus: Interpretable Modeling of Mental Health Dynamics from Social Media Timelines using Hybrid Rule-Based and RAG Methods

We present DreamerNLplus, a hybrid framework for modeling mental health dynamics from social media timelines in the CLPsych 2026 shared task. Our system addresses three tasks: psyc…

16 views ·
#mental health#social media#machine learning
DEV.TO (TOP)

LMR-BENCH: Can LLM Agents Reproduce NLP Research Code? (EMNLP 2025)

LMR-BENCH (EMNLP 2025) benchmarks LLM agents on reproducing code from 23 NLP papers. This PoC explains the masking methodology, evaluation axes, and what the results mean for AI-as…

13 views ·
#research#llm
ARXIV CS.AI

Retrieval-Augmented Long-Context Translation for Cultural Image Captioning: Gators submission for AmericasNLP 2026 shared task

We present the University of Florida Gators submission to the AmericasNLP 2026 shared task on cultural image captioning for Indigenous languages. Our two-stage pipeline generates a…

18 views ·
#language#artificial intelligence#computer vision
DEV.TO (TOP)

92. BERT: The Model That Reads in Both Directions

GPT generates text by predicting the next word. It reads left to right. BERT does something...…

12 views ·
#ai#programming
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Python Sentiment Analysis: From Basics to BERT

` Imagine opening your laptop and seeing 5,000 product reviews, hundreds of support tickets, and a...…

14 views ·
#python#datascience
DEV.TO (TOP)

LLMs as Linguistic Probes: A Graduate Student's Guide to Advanced Syntax, Semantics, and Efficient Fine-Tuning

The intersection of large language models (LLMs) and advanced linguistics has moved beyond...…

18 views ·
#computational linguistics#nlp research#large language models
DEV.TO (TOP)

How I keep LLMs on a tight leash and stopped hand-creating 30 GitHub issues in the process

The way I keep LLMs on a tight leash is through structured issue breakdowns. In this post you'll see...…

16 views ·
#productivity#github#python
DEV.TO (TOP)

I Added Three Rules to Gemma 4. The MoE Searched. The Dense Model Refused.

I ran Gemma 4 26B (MoE, 4B active) and Gemma 4 31B (dense) against GPT-4o and GPT-4o mini on a real Arabic e-commerce chatbot. Then I added three Gemma-only prompt rules. The MoE v…

12 views ·
#ai#llm#opensource