The Top AI Papers of the Week (January 12-18) – UniversalRAG
– Agent-as-a-Judge
– Self-Evolving Search Agents
– Active Context Compression
– Efficient Lifelong Memory for LLM Agents
– Extending Context by Dropping Positional Embeddings
– Unified Long-Term and Short-Term Memory
LLMS
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Top AI Research Papers: RAG, Agents, and Memory Optimization
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Claude Mastery Guide: How to Prompt It Correctly
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Claude is the smartest AI right now. But 90% of people prompt it like ChatGPT. That's why I made the Claude Mastery Guide: → How Claude thinks differently
→ Prompts built for Claude
→ Workflows that use its strengths Comment "Claude" and I'll DM it free. -
AI Accelerates Scientific Progress Solving Unsolvable Math Problems
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Nous observons les premiers signes d’une accélération ×1000 du progrès scientifique et technologique, portée par l’IA. L’IA résout désormais des problèmes mathématiques extrêmement difficiles (presque chaque jour) que les humains n’avaient jamais réussi à résoudre jusqu’ici. Ce
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Unencrypted data in LLM tools poses security risk
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Most tools I've seen don't encrypt your data going into the LLMs (meaning someone could listen if they had the smarts).
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Advanced LLMs Integration: Beyond Claude and GPT Capabilities
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To begin with, it uses way more powerful LLMs like Claude and GPT – but it's a lot more that just that –
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LLMs Replace Hand-Crafted Rewards in Multi-Agent RL
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A huge claim from this paper on the end of reward engineering. Reward engineering remains a persistent bottleneck in multi-agent RL. This paper argues that LLMs enable a fundamental shift: from hand-crafted reward functions to natural language objectives. If language can
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ChatLLM: Instant URL Summarization and Content Generation
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Drop a URL into ChatLLM by Abacus AI
— Abacus.AI (@abacusai) 17 janvier 2026
It scrapes the page, summarizes it in seconds, and lets you turn it into a PDF or even generate quizzes from it.
Reading just got a lot faster. pic.twitter.com/c0LbLiNd55Drop a URL into ChatLLM by Abacus AI It scrapes the page, summarizes it in seconds, and lets you turn it into a PDF or even generate quizzes from it. Reading just got a lot faster.
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Alibaba-backed AI (100M users) launches omni-model, memory attention, instant generation
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Alibaba-backed. 100M users. Launched Jan 13.
— God of Prompt (@godofprompt) 17 janvier 2026
Three breakthroughs nobody else has:
Omni-model (everything speaks one language)
Memory attention (infinite worlds that remember)
1-4 step generation (instant response)
They unified what Google, OpenAI, Meta built separately. pic.twitter.com/irDCNCm78ZAlibaba-backed. 100M users. Launched Jan 13.
Three breakthroughs nobody else has: Omni-model (everything speaks one language)
Memory attention (infinite worlds that remember)
1-4 step generation (instant response) They unified what Google, OpenAI, Meta built separately. -
C2C outperforms traditional Text-to-Text on four benchmarks
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8. C2C was rigorously tested on four major challenges: MMLU-Redux, OpenBookQA, ARC-Challenge, and C-Eval. It significantly outperformed the traditional "Text-to-Text" approach.
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C2C introduces neural Fuser to connect model KV-Caches
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5. Each model possesses a memory storage referred to as KV-Cache. C2C introduces a small neural "Fuser" that connects the memory of one model to another, facilitating information sharing and collaboration.