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AI Research Today unpacks the latest advancements in artificial intelligence, one paper at a time. We go beyond abstracts and headlines, walking through architectures, experiments, training details, ablations, failure modes, and the implications for future work. Each episode will choose between one and three new, impactful research papers and go through them in depth. We will discuss the papers at the level of an industry practitioner or AI researcher. If you want to understand the newest topics in AI research but don't have the time to dig through the papers yourself, this is your solution.
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Recent Episodes
S1E12 Generative Recursive Reasoning
Send us Fan MailIn this episode, we explore the paper "Generative Recursive Reasoning (GRAM)," a fascinating new approach to AI reasoning co-authored by Yoshua Bengio and researchers from Mila and…
S1E10 OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language Environment Simulation
Send us Fan MailIn this episode, we break down the new paper “OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language Environment Simulation,” which explores how AI agents can…
GradMem: Teaching LLMs to Remember (Without Retraining)
Send us Fan MailIn this episode, we break down GradMem, a new approach to memory in large language models: https://arxiv.org/pdf/2603.13875v1Instead of relying on the transformer KV cache or…
Language Models are Injective and Hence Invertible
Send us Fan MailIn this episode, we break down a fascinating new result from recent research: that modern Transformer language models are almost surely injective—meaning different prompts map to…
S1E7 Learning to Reason in 13 Parameters
Send us Fan MailLink to arxiv: https://arxiv.org/pdf/2602.04118Large language models have recently shown impressive reasoning abilities, often learned through reinforcement learning and low-rank…
S1E6 SPIRAL: Symbolic LLM Planning via Grounded and Reflective Search
Send us Fan MailLarge Language Models often struggle with complex planning tasks that require exploration, backtracking, and self-correction. Once an LLM commits to an early mistake, its linear…
S1E5 Meta-RL Induces Exploration In Language Agents
Send us Fan MailEpisode Paper: https://arxiv.org/pdf/2512.16848In this episode, we dive into a cutting-edge AI research breakthrough that tackles one of the biggest challenges in training intelligent…
S1E4 DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
Send us Fan MailIn this episode, we unpack DeepSearch, a new paradigm in reinforcement learning with verifiable rewards (RLVR) that aims to overcome one of the biggest bottlenecks in training…
S1E3 Transformer-Squared: Self-Adaptive LLMs
Send us Fan MailIn this episode we’re diving into “Transformer-Squared: Self-Adaptive LLMs” — a new framework for adapting large language models to unseen tasks on the fly by tuning only a small part…
S1E2 Nested Learning: The Illusion of Deep Learning Architectures
Send us Fan Mail NL.pdfIn this episode, we dive into Nested Learning (NL) — a new framework that rethinks how neural networks learn, store information, and even modify themselves. While modern…
S1E1 AgentEvolver: An Autonomous Agent Framework
Send us Fan Mailhttps://arxiv.org/pdf/2511.10395What if AI agents could teach themselves? In this episode, we dive into AgentEvolver, a groundbreaking framework from Alibaba's Tongyi Lab that flips…
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AI Research Today has published 11 episodes since November 2025, covering topics in Science.
AI Research Today is currently highly active with new episodes monthly. Average episode length is 34m.
