Natural Language Processing

Text understanding and language tasks

Top This Week

Llms

The Claude Code leak accidentally published the first complete blueprint for production AI agents. Here's what it tells us about where this is all going.

Most coverage of the Claude Code leak focuses on the drama or the hidden features. But the bigger story is that this is the first time we...

Reddit - Artificial Intelligence · 1 min ·
Llms

[For Hire] Junior AI/ML Engineer | RAG · LLMs · FastAPI · Vector DBs | Remote

Posting this for a friend who isn't on Reddit. A recent graduate, entry level, no commercial production experience but spent the past yea...

Reddit - ML Jobs · 1 min ·
Llms

Agents Can Now Propose and Deploy Their Own Code Changes

150 clones yesterday. 43 stars in 3 days. Every agent framework you've used (LangChain, LangGraph, Claude Code) assumes agents are tools ...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2603.01822] Emerging Human-like Strategies for Semantic Memory Foraging in Large Language Models
Llms

[2603.01822] Emerging Human-like Strategies for Semantic Memory Foraging in Large Language Models

Abstract page for arXiv paper 2603.01822: Emerging Human-like Strategies for Semantic Memory Foraging in Large Language Models

arXiv - AI · 4 min ·
[2603.01801] What Papers Don't Tell You: Recovering Tacit Knowledge for Automated Paper Reproduction
Nlp

[2603.01801] What Papers Don't Tell You: Recovering Tacit Knowledge for Automated Paper Reproduction

Abstract page for arXiv paper 2603.01801: What Papers Don't Tell You: Recovering Tacit Knowledge for Automated Paper Reproduction

arXiv - AI · 3 min ·
[2603.01783] GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generation
Llms

[2603.01783] GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generation

Abstract page for arXiv paper 2603.01783: GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generation

arXiv - AI · 4 min ·
[2603.01620] ToolRLA: Fine-Grained Reward Decomposition for Tool-Integrated Reinforcement Learning Alignment in Domain-Specific Agents
Machine Learning

[2603.01620] ToolRLA: Fine-Grained Reward Decomposition for Tool-Integrated Reinforcement Learning Alignment in Domain-Specific Agents

Abstract page for arXiv paper 2603.01620: ToolRLA: Fine-Grained Reward Decomposition for Tool-Integrated Reinforcement Learning Alignment...

arXiv - AI · 3 min ·
[2603.01571] Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models
Machine Learning

[2603.01571] Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models

Abstract page for arXiv paper 2603.01571: Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models

arXiv - AI · 4 min ·
[2603.01511] Multimodal Mixture-of-Experts with Retrieval Augmentation for Protein Active Site Identification
Machine Learning

[2603.01511] Multimodal Mixture-of-Experts with Retrieval Augmentation for Protein Active Site Identification

Abstract page for arXiv paper 2603.01511: Multimodal Mixture-of-Experts with Retrieval Augmentation for Protein Active Site Identification

arXiv - AI · 3 min ·
[2603.01486] Agentic Multi-Source Grounding for Enhanced Query Intent Understanding: A DoorDash Case Study
Llms

[2603.01486] Agentic Multi-Source Grounding for Enhanced Query Intent Understanding: A DoorDash Case Study

Abstract page for arXiv paper 2603.01486: Agentic Multi-Source Grounding for Enhanced Query Intent Understanding: A DoorDash Case Study

arXiv - AI · 4 min ·
[2603.01410] GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning
Llms

[2603.01410] GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Graph Reasoning

Abstract page for arXiv paper 2603.01410: GraphScout: Empowering Large Language Models with Intrinsic Exploration Ability for Agentic Gra...

arXiv - AI · 4 min ·
[2603.01407] The Observer-Situation Lattice: A Unified Formal Basis for Perspective-Aware Cognition
Nlp

[2603.01407] The Observer-Situation Lattice: A Unified Formal Basis for Perspective-Aware Cognition

Abstract page for arXiv paper 2603.01407: The Observer-Situation Lattice: A Unified Formal Basis for Perspective-Aware Cognition

arXiv - AI · 4 min ·
[2603.01227] The Lattice Representation Hypothesis of Large Language Models
Llms

[2603.01227] The Lattice Representation Hypothesis of Large Language Models

Abstract page for arXiv paper 2603.01227: The Lattice Representation Hypothesis of Large Language Models

arXiv - AI · 3 min ·
[2603.01160] Semantic XPath: Structured Agentic Memory Access for Conversational AI
Machine Learning

[2603.01160] Semantic XPath: Structured Agentic Memory Access for Conversational AI

Abstract page for arXiv paper 2603.01160: Semantic XPath: Structured Agentic Memory Access for Conversational AI

arXiv - AI · 3 min ·
[2603.01152] DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent
Machine Learning

[2603.01152] DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent

Abstract page for arXiv paper 2603.01152: DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent

arXiv - AI · 3 min ·
[2603.01055] MMCOMET: A Large-Scale Multimodal Commonsense Knowledge Graph for Contextual Reasoning
Nlp

[2603.01055] MMCOMET: A Large-Scale Multimodal Commonsense Knowledge Graph for Contextual Reasoning

Abstract page for arXiv paper 2603.01055: MMCOMET: A Large-Scale Multimodal Commonsense Knowledge Graph for Contextual Reasoning

arXiv - AI · 3 min ·
[2603.00808] MetaMind: General and Cognitive World Models in Multi-Agent Systems by Meta-Theory of Mind
Machine Learning

[2603.00808] MetaMind: General and Cognitive World Models in Multi-Agent Systems by Meta-Theory of Mind

Abstract page for arXiv paper 2603.00808: MetaMind: General and Cognitive World Models in Multi-Agent Systems by Meta-Theory of Mind

arXiv - AI · 4 min ·
[2603.00873] MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains
Llms

[2603.00873] MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains

Abstract page for arXiv paper 2603.00873: MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Ch...

arXiv - AI · 4 min ·
[2603.00599] Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger
Machine Learning

[2603.00599] Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger

Abstract page for arXiv paper 2603.00599: Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger

arXiv - Machine Learning · 4 min ·
[2603.00465] Optimizing In-Context Demonstrations for LLM-based Automated Grading
Llms

[2603.00465] Optimizing In-Context Demonstrations for LLM-based Automated Grading

Abstract page for arXiv paper 2603.00465: Optimizing In-Context Demonstrations for LLM-based Automated Grading

arXiv - AI · 4 min ·
[2603.00460] MED-COPILOT: A Medical Assistant Powered by GraphRAG and Similar Patient Case Retrieval
Llms

[2603.00460] MED-COPILOT: A Medical Assistant Powered by GraphRAG and Similar Patient Case Retrieval

Abstract page for arXiv paper 2603.00460: MED-COPILOT: A Medical Assistant Powered by GraphRAG and Similar Patient Case Retrieval

arXiv - AI · 4 min ·
[2603.00349] EmCoop: A Framework and Benchmark for Embodied Cooperation Among LLM Agents
Llms

[2603.00349] EmCoop: A Framework and Benchmark for Embodied Cooperation Among LLM Agents

Abstract page for arXiv paper 2603.00349: EmCoop: A Framework and Benchmark for Embodied Cooperation Among LLM Agents

arXiv - AI · 4 min ·
[2603.00267] Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
Machine Learning

[2603.00267] Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking

Abstract page for arXiv paper 2603.00267: Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking

arXiv - AI · 4 min ·
Previous Page 56 Next

Related Topics

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Daily or weekly digest • Unsubscribe anytime