AI·Virginia Tech researchers found that resistance training (modeled as mouse weightlifting) outperforms running for reducing fat and improving insulin sensitivity and glucose control in obesity and Type 2 diabetes models.
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AI·OpenAI released GPT-5.6 in three tiers—Sol (flagship), Terra, and Luna—boosting benchmarks in Agent's Last Exam (56.3 score), math, coding, security, and research while slashing token costs and adding Max/Ultra reasoning modes.
AI·Anthropic's J-space analysis of Claude reveals a small subset of internal representations forming a functional global workspace for flexible reasoning, but the paper explicitly states this has no bearing on AI consciousness and clarifies the core of AI alignment research.
AI·Zhipu AI founder Tang Jie releases internal letter after 'GLM Moment' success, announcing focus on long-horizon tasks, autonomous agents, and self-evolving AI beyond coding and reasoning.
AI·AI is tested in real disaster simulations like fires, evacuations, and crowds to assess decision-making, collaboration, and survival ability rather than human-like appearance.
AI·This position paper reviews LLM-driven formal theorem provers and argues that current systems function mainly as solvers for well-defined problems, not as research agents capable of discovering new theorems or resolving open conjectures at the frontier. It identifies key limitations in datasets, exploration, tools, and collaboration and proposes a roadmap for AI4Math systems to support genuine mathematical research.
AI·XALPHA is a memory-driven AI quant researcher that uses multi-source research memory integrating external financial reports and prior discovery feedback, with Macro Brain for theme planning and archetype selection, Micro Brain for hypothesis-to-code translation and tri-alignment verification, and Cross Brain for feedback consolidation, enabling closed-loop continuous alpha discovery that outperforms baselines on CSI300.
AI·Researchers developed SQZ-Qwen-ASR-1.7B for MLC-SLM 2026 Task 1, combining a modular speaker diarization front-end (VAD, CAMPPlus embeddings, spectral clustering, RTTM segmentation) with Qwen3-ASR-1.7B adapted via full supervised fine-tuning, LoRA on TTS-generated synthetic speech, and GRPO reinforcement learning for lower tcpMER (23.70 on dev set, 17.97 on eval set).
AI·The research finds that preprocessing-based stereotype mitigation in NLP can backfire by increasing stereotyping or counter-stereotyping for some groups relative to neutral baselines.
AI·Formal verification method using ESBMC-PLC+ detects Ladder Logic Bombs in IEC 61131-3 PLC programs by focusing on function-block bodies where malicious code hides.
AI·Procrustes-conditioned Joint End-to-end Top-K Sparse Autoencoders extract cross-seed universal features from independently trained BERT models to address dictionary learning misalignment in mechanistic interpretability.
AI·Structured pruning method for sparsely-activated MoE models removes bad experts to address full expert bank memory bottleneck while preserving inference efficiency.
AI·The paper presents a cost-efficient human-LLM collaborative annotation framework to construct the EspanSt stereotype dataset for non-English languages and underrepresented cultures.
I am currently working across multiple research communities, and I've noticed that the ML community is struggling with a massive volume of submissions, which is affecting review quality (as we are seeing in the recent ARR cycles). I am wondering what the reasoning is for not limiting the number of submissions per author? This practice has been successfully used in other research areas for years, …
A new analysis from OpenAI reveals issues in SWE-Bench Pro, a popular coding benchmark, raising concerns about reliability and accuracy in evaluating AI models.
Lately in the last two/three years, I have noticed ICML, Neurips becoming more prestigious than the actual journals. What is the actual reason of this culture? Is this due to the AI boom and rising demand and the fact that conferences have a higher and a faster acceptance rate as compared to journals and with the growing hype they need to deliver things faster? What do you all think? submitted by…
Introducing GeneBench-Pro, a new benchmark testing AI performance in genomics, biology, and scientific research using complex, real-world datasets.
A new OpenAI research paper shows how AI agents are transforming work, enabling longer, more complex tasks and expanding productivity across roles.
GPT-5 Pro helped solve a 3-year-old immunology mystery, offering insights into T cell behavior. The breakthrough could support cancer and autoimmune research.
Researchers used an OpenAI reasoning model to help diagnose rare diseases, identifying 18 new diagnoses in previously unsolved cases.
OpenAI and Molecule.one show how a near-autonomous AI chemist using GPT-5.4 improved a key drug-making reaction, advancing medicinal chemistry research.
Introducing LifeSciBench, an expert-authored, expert-reviewed benchmark for evaluating how AI systems handle real-world life science research tasks and decisions.
OpenAI introduces Deployment Simulation, a method to predict AI model behavior before deployment using real conversation data to improve safety and evaluation accuracy.
Google DeepMind and partners announce a $10M funding call for multi-agent safety research.
Calico Life Sciences uses Co-Scientist to connect scattered findings and generate new leads in aging research.
Introducing Co-Scientist, a collaborative AI partner built with Gemini to help researchers accelerate scientific breakthroughs.
Researching the path to AI-augmented care and development of an AI co-clinician.
Google DeepMind researches AI's harmful manipulation risks across areas like finance and health, leading to new safety measures.
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Embodied agents are typically built as hand-designed compositions of perception, memory, planning, and action modules. This modularity exposes a large architectural design space, but current systems still rely on researcher intuition to choose where information is stored, how observations are processed, and how model calls are connected. Agent Architecture Search (AAS) automates such design for text-domain agents, but has not been systematically evaluated on perceptual embodied agents through s…