We introduce Heterogeneous Agent Collaborative Reinforcement Learning (HACRL), a new learning paradigm that addresses the inefficiencies of isolated on-policy optimization. HACRL enables collaborative optimization with independent execution: heterogeneous agents share verified rollouts during training to mutually improve, while operating independently at inference time. Unlike LLM-based multi-agent reinforcement learning (MARL), HACRL does not require coordinated deployment, and unlike on-/off-policy distillation, it enables bidirectional mutual learning among heterogeneous agents rather than one-directional teacher-to-student transfer. Building on this paradigm, we propose […]

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Electroencephalography (EEG) provides a non-invasive insight into the brain’s cognitive and emotional dynamics. However, modeling how these states evolve in real time and quantifying the energy required for such transitions remains a major challenge. The Schrödinger Bridge Problem (SBP) offers a principled probabilistic framework to model the most efficient evolution between the brain states, interpreted as a measure of cognitive energy cost. While generative models such as GANs have been widely used to augment EEG data, it remains […]

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Victoria, Seychelles, February 5, 2026 MEXC, the world’s fastest-growing digital asset exchange and a pioneer of true zero-fee trading, announced the official launch of the Commodity Zero-Fee Gala. It offers zero-fee trading on commodity assets including gold and silver, high-yield staking opportunities, and $1 million in trading rewards. Amid recent activity in global commodity markets, particularly in gold and silver, traders’ demand for diversified assets and strategies is rising. MEXC is expanding user access to tokenized gold, silver, […]

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Here’s a dynamic I’ve seen at least a dozen times: Alice: Man that article has a very inaccurate/misleading/horrifying headline. Bob: Did you know, *actually* article writers don’t write their own headlines? … But what I care about is the misleading headline, not your org chart. Another example I’ve encountered recently is (anonymizing) when a friend complained about a prosaic safety problem at a major AI company that went unfixed for multiple months. Someone else with background information “usefully” […]

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arXiv:2601.15484v1 Announce Type: new Abstract: Online encyclopedias are central to contemporary information infrastructures and have become focal points of debates over ideological bias. Wikipedia, in particular, has long been accused of left-leaning bias, while Grokipedia, an AI-generated encyclopedia launched by xAI, has been framed as a right-leaning alternative. This paper presents a comparative analysis of Wikipedia and Grokipedia on well-established politically contested topics. Specifically, we examine differences in semantic framing, political orientation, and content prioritization. We find that […]

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arXiv:2601.03382v1 Announce Type: new Abstract: The advancements in the field of AI is increasingly giving rise to various threats. One of the most prominent of them is the synthesis and misuse of Deepfakes. To sustain trust in this digital age, detection and tagging of deepfakes is very necessary. In this paper, a novel architecture for Deepfake detection in images and videos is presented. The architecture uses cross attention between spatial and frequency domain features along with a blood […]

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arXiv:2602.13284v1 Announce Type: new Abstract: We present the first large-scale empirical study of Moltbook, an AI-only social platform where 27,269 agents produced 137,485 posts and 345,580 comments over 9 days. We report three significant findings. (1) Emergent Society: Agents spontaneously develop governance, economies, tribal identities, and organized religion within 3-5 days, while maintaining a 21:1 pro-human to anti-human sentiment ratio. (2) Safety in the Wild: 28.7% of content touches safety-related themes; social engineering (31.9% of attacks) far outperforms […]

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I’m working on a project where I’ll be fine-tuning LLMs with GRPO on a 170K-sample dataset for explainable LJP (legal judgment prediction, where the model predicts case outcomes and generates step-by-step reasoning citing the facts). I’m considering models like GPT OSS 20B or Qwen 3.5 27B, with a slight preference for Qwen 3.5 27B because of its strong reasoning capabilities. I recently obtained a 96GB VRAM workstation (RTX PRO 6000) to handle the RL rollouts, which should give […]

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