Rohan Paul (@rohanpaul_ai)
Absolutely classic @GoogleResearch paper on In-Context-Learning by LLMs. Shows the mechanisms of how LLMs learn in context from examples in the prompt, can pick up new patterns while answering, yet their stored weights never change. 💡The mechanism they reveal for in-context-learning. When the ...
LLM for financial trading/decision making. A 4B model financial-domain model, Trading-R1, that writes clear analyst theses and turns them into trades. Its trained on 100K cases over 18 months across 14 tickers, and its backtests show better risk-adjusted returns with smaller drawdowns. The probl...
One of the best paper of the recent week. The big takeaway: scaling up model size doesn’t just make models smarter in terms of knowledge, it makes them last longer on multi-step tasks, which is what really matters for agents. Shows that small models can usually do one step perfectly, but when you ...
🚨 BREAKING: The 2nd research proves Generative AI is lowering demand for junior staff, though senior jobs are still secure. 7.7% junior headcount decline within generative-AI adopters firms by 6 quarters, and 40% fewer junior hires per quarter in wholesale and retail. They used U.S. résumé and job...
"The Impact of Artificial Intelligence on Human Thought" A big 132 page report. AI is shifting real thinking work onto external systems, which boosts convenience but can weaken the effort that builds understanding and judgment, A pattern the paper frames through cognitive offloading and cognitive...
The paper shows how an LLM agent keeps improving by learning from its own memory, without changing the base model. It ranks top on GAIA validation at 87.88% Pass@3, with 79.40% on the private test. Most agent systems either rely on fixed workflows that never adapt, or burn compute to fine tune mo...
Its going viral on Reddit. Somebody let ChatGPT run a $100 live share portfolio, restricted to U.S. micro-cap stocks. Did an LLM really bit the market?. - 4 weeks +23.8% while the Russell 2000 and biotech ETF XBI rose only ~3.9% and 3.5%. Prompt + GitHub posted --- ofcourse its a short‑term ...
MASSIVE claim in this paper. AI Architectural breakthroughs can be scaled computationally, transforming research progress from a human-limited to a computation-scalable process. So it turns architecture discovery into a compute‑bound process, opening a path to self‑accelerating model evolution w...
MapReduce meets LLMs: Divide-and-conquer approach lets regular LLMs process 100x longer documents than their context limit Using MapReduce principles, small-context LLMs now handle million-token documents efficiently. Original Problem 🔍: LLMs struggle to process extremely long texts exceeding the...