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PaperAgent

Daily updates, analyzing cutting-edge AI research papers

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PaperAgent
PaperAgent
May 23, 2026 · Artificial Intelligence

Why Large Language Models Can't Achieve Consciousness, According to Google

Google DeepMind researchers argue that, contrary to popular speculation, AI systems cannot possess consciousness because consciousness is a physical phenomenon that precedes computation, and the prevailing computational functionalism mistakenly treats computation as the bridge to consciousness, leading to a flawed ontological inversion.

AI consciousnessAI safetycomputational functionalism
0 likes · 8 min read
Why Large Language Models Can't Achieve Consciousness, According to Google
PaperAgent
PaperAgent
May 22, 2026 · Artificial Intelligence

A Systematic Review of the Latest Auto‑Research Landscape

The article presents a four‑phase, eight‑stage systematic analysis of AI‑driven auto‑research, exposing reliability gaps, bottlenecks, and best‑practice deployment through human‑governed collaboration, while detailing benchmarks, failure modes, and architectural families.

AI research automationauto-researchevaluation benchmarks
0 likes · 11 min read
A Systematic Review of the Latest Auto‑Research Landscape
PaperAgent
PaperAgent
May 21, 2026 · Artificial Intelligence

Anthropic’s Claude Code Harness: Best Practices for AI Coding in Large Codebases

Anthropic’s applied‑AI team found that the success of Claude Code in million‑line monorepos and multi‑repo microservice environments depends far more on a well‑engineered harness—such as layered CLAUDE.md files, hooks, skills, plugins, LSP integration, MCP servers and sub‑agents—than on the underlying model itself.

AI programming toolsAnthropicClaude Code
0 likes · 10 min read
Anthropic’s Claude Code Harness: Best Practices for AI Coding in Large Codebases
PaperAgent
PaperAgent
May 21, 2026 · Artificial Intelligence

238 Promising Reinforcement‑Learning Ideas Likely to Earn CCF‑A Papers in 2026

The article compiles 238 cutting‑edge reinforcement‑learning ideas across 21 research directions, highlights recent breakthroughs such as Sutton’s Intentional Updates, and provides brief overviews of representative papers—including knowledge‑graph, Kalman‑filter, agentic, LLM‑driven, and world‑model approaches—along with links to the accompanying source code.

Kalman filterLLMWorld Models
0 likes · 6 min read
238 Promising Reinforcement‑Learning Ideas Likely to Earn CCF‑A Papers in 2026
PaperAgent
PaperAgent
May 19, 2026 · Artificial Intelligence

Why Long-Term Memory Needs Vision: How MemEye Evaluates Multimodal Agent Recall

MemEye is a multimodal memory benchmark that tests agents across eight real‑world scenarios, measuring visual evidence granularity and reasoning depth, and reveals that captions fall short for fine‑grained visual recall, highlighting the need for true visual memory in long‑term AI agents.

AI agentsEvaluationMemEye
0 likes · 4 min read
Why Long-Term Memory Needs Vision: How MemEye Evaluates Multimodal Agent Recall
PaperAgent
PaperAgent
May 18, 2026 · Artificial Intelligence

How MemWeaver Combines Behavioral and Cognitive Memory to Rebuild LLM Personalization

MemWeaver introduces a hierarchical memory that fuses behavior‑level and cognition‑level user signals, enabling large language models to generate more personalized content across multiple tasks, with extensive experiments, ablations, and an efficient incremental update mechanism demonstrating superior performance over strong baselines.

LLM personalizationLaMP benchmarkbehavioral memory
0 likes · 12 min read
How MemWeaver Combines Behavioral and Cognitive Memory to Rebuild LLM Personalization
PaperAgent
PaperAgent
May 17, 2026 · Artificial Intelligence

Turning LLMs into CT Scans: How Alibaba’s Safe‑SAIL Makes AI Decision Black Boxes Transparent

The paper introduces Safe‑SAIL, a Sparse Autoencoder Interpretation Framework for LLMs that provides pre‑explanation metrics, a segment‑level simulation to cut evaluation cost, and a 1,758‑feature safety database, enabling transparent analysis and interactive debugging of large language model safety decisions.

LLMSafe‑SAILSparse Autoencoder
0 likes · 12 min read
Turning LLMs into CT Scans: How Alibaba’s Safe‑SAIL Makes AI Decision Black Boxes Transparent
PaperAgent
PaperAgent
May 16, 2026 · Artificial Intelligence

A First Systematic Survey of Agent Skills: Taxonomy, Techniques, and Applications

This survey analyzes the emerging field of Agent Skills, defining a formal skill model, categorizing acquisition pathways, detailing retrieval strategies, and outlining a five‑stage evolution process, while highlighting large‑scale skill repositories and their implications for AI product design.

AI agentsAgent skillsSkill Evolution
0 likes · 9 min read
A First Systematic Survey of Agent Skills: Taxonomy, Techniques, and Applications
PaperAgent
PaperAgent
May 15, 2026 · Artificial Intelligence

How a 0.6B Model Beats GPT‑5.2 at Agent Privacy – Introducing MemPrivacy

The article analyzes the long‑standing privacy dilemma of cloud‑based agents, presents MemPrivacy’s three‑stage de‑identification framework and four‑level privacy taxonomy, details its two‑phase training with the MemPrivacy‑Bench dataset, and shows benchmark results where a 0.6B model outperforms GPT‑5.2 while keeping latency under 0.5 seconds.

AgentMemPrivacybenchmark
0 likes · 11 min read
How a 0.6B Model Beats GPT‑5.2 at Agent Privacy – Introducing MemPrivacy