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PaperAgent

Daily updates, analyzing cutting-edge AI research papers

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PaperAgent
PaperAgent
Aug 4, 2026 · Artificial Intelligence

Tencent’s WorkBuddy Unveils Its Internal Benchmark in a New Paper

Tencent’s WorkBuddy team released a paper describing the open‑source WorkBuddy Bench, a multi‑model agent benchmark that details task generation, contamination prevention, four specialized tracks (Code, Web, Office, Security), and extensive leaderboard results that reveal how models like GLM‑5.2, Opus 4.8 and GPT‑5.5 perform across diverse real‑world scenarios.

AI BenchmarkAgentic AILLM evaluation
0 likes · 13 min read
Tencent’s WorkBuddy Unveils Its Internal Benchmark in a New Paper
PaperAgent
PaperAgent
Aug 2, 2026 · Artificial Intelligence

OpenWorker: Andrew Ng’s Open‑Source AI Coworker Hits 11K Stars

OpenWorker, an open‑source AI coworker released by Andrew Ng, delivers finished work such as HTML briefings by integrating with tools like HubSpot and Slack, supports multiple models, offers 25+ connectors, and enforces approval for risky actions, positioning it as a self‑hosted alternative to Tencent's WorkBuddy.

AI coworkerApproval WorkflowOpenWorker
0 likes · 7 min read
OpenWorker: Andrew Ng’s Open‑Source AI Coworker Hits 11K Stars
PaperAgent
PaperAgent
Aug 2, 2026 · Artificial Intelligence

OpenAI Unveils Astra: A New Model Solving Ten Decades‑Old Math Problems

OpenAI's quietly released Astra model, revealed through a math paper, claims to have solved ten long‑standing open problems across mathematics and theoretical computer science, generating proofs with the model itself and formalising them in Lean for verification.

AI AgentsAstraLarge Language Model
0 likes · 5 min read
OpenAI Unveils Astra: A New Model Solving Ten Decades‑Old Math Problems
PaperAgent
PaperAgent
Aug 1, 2026 · Artificial Intelligence

How to Run DeepSeek‑V4‑Flash Locally on a 100 GB Server: Best‑Practice Guide

The article details the release of DeepSeek‑V4‑Flash‑0731, explains how its 284 B‑parameter, 13 B‑activated model can run losslessly on a machine with only 169 GB RAM using Unsloth’s UD‑Q8_K_XL quantization, compares quantization quality, and provides step‑by‑step deployment instructions via Unsloth Studio and llama.cpp.

AI Model DeploymentDeepSeek-V4-FlashLossless Quantization
0 likes · 7 min read
How to Run DeepSeek‑V4‑Flash Locally on a 100 GB Server: Best‑Practice Guide
PaperAgent
PaperAgent
Aug 1, 2026 · Artificial Intelligence

Why LLMs Remember Yet Forget: The Cost of Evolving User Intent

Microsoft Research reveals that large language models excel on static single‑turn tasks but dramatically lose accuracy when user intent evolves across multiple turns, especially during function switches; the study formalizes three intent transition types, proposes a backward‑generation framework, and shows modest gains from memory mechanisms while highlighting the need for active intent recaps.

LLMMemory MechanismMulti-turn Dialogue
0 likes · 12 min read
Why LLMs Remember Yet Forget: The Cost of Evolving User Intent
PaperAgent
PaperAgent
Jul 29, 2026 · Artificial Intelligence

How to Build Harness‑Native Agents Using OpenForge RL

OpenForge RL introduces a lightweight proxy and Kubernetes‑based orchestrator to decouple training from inference, enabling the training of 30B‑scale and 8B agents within any harness, while providing an automatic five‑stage task synthesis pipeline and demonstrating state‑of‑the‑art results across Claw, GUI, and Browser benchmarks.

AgentHarnessKubernetes
0 likes · 13 min read
How to Build Harness‑Native Agents Using OpenForge RL
PaperAgent
PaperAgent
Jul 28, 2026 · Artificial Intelligence

Inside Anthropic’s New Graph Engineering Methodology for Multi‑Agent Systems

Anthropic’s recent 12‑page playbook and 2‑hour workshop detail a Graph Engineering pipeline that replaces costly context‑window communication with a shared knowledge graph, covering why windows fail, a four‑stage Claude API workflow, extraction rules, entity resolution, graph assembly, multi‑hop querying, integration into five agent modes, cost analysis, scaling strategies, and guidance on when not to use a knowledge graph.

Agentic AIAnthropicClaude API
0 likes · 14 min read
Inside Anthropic’s New Graph Engineering Methodology for Multi‑Agent Systems
PaperAgent
PaperAgent
Jul 27, 2026 · Artificial Intelligence

Why Dropping 80% of System Prompts Improves Claude 5: New Context Engineering Rules

Anthropic’s official Claude 5 guide reveals that removing most Claude Code system prompts has no measurable impact, overturning traditional context‑engineering practices and introducing six paradigm shifts that let the model rely on its own judgment and progressive context loading.

AI AgentsAnthropicClaude-5
0 likes · 6 min read
Why Dropping 80% of System Prompts Improves Claude 5: New Context Engineering Rules
PaperAgent
PaperAgent
Jul 27, 2026 · Artificial Intelligence

Dual‑Engine Evolution: A Systematic Survey of Long‑Horizon Agents

This 149‑page survey defines long‑horizon agents as a coupling of a base policy and a runtime harness (Agent = πθ ⊕ H), categorises task levels and capabilities, traces the field’s evolution from prompt to context to runtime engineering, and outlines a seven‑stage optimization pipeline, application forms, and frontier challenges, supported by empirical growth data and extensive references.

AI SurveyAgent optimizationAgentic AI
0 likes · 12 min read
Dual‑Engine Evolution: A Systematic Survey of Long‑Horizon Agents