Knowledge catalogue
arXiv:2604.14158v1 Announce Type: new Abstract: Current evaluations of long-term memory in LLMs are fundamentally static. By fixating on simple retrieval and short-context inference, they neglect the
Atelier is a canvas-like system that leverages generative image and video models to blend spaces for thinking and creation, where both references and generated assets co-exist in one unified workspace
arXiv:2604.13206v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into agentic workflows, their unpredictability stemming from numerical instability has eme
arXiv:2604.14017v1 Announce Type: cross Abstract: Under interpolation-type assumptions such as the strong growth condition, stochastic optimization methods can attain convergence rates comparable to f
arXiv:2604.13552v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong reasoning capabilities, but their performance often degrades under distribution shift. Existing test-tim
arXiv:2604.13016v1 Announce Type: cross Abstract: On-policy distillation (OPD) has become a core technique in the post-training of large language models, yet its training dynamics remain poorly unders
arXiv:2604.10506v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have made significant strides in static image understanding but continue to face critical hurdles in spatiotemporal reason
arXiv:2604.10697v1 Announce Type: new Abstract: Large language models frequently exhibit hallucinations: fluent and confident outputs that are factually incorrect or unsupported by the input context.
arXiv:2604.10219v1 Announce Type: new Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved remarkable strides in visual reasoning through test time compute scaling, yet long chain reasoni
GMI Cloud and @Zai_org are bringing fast inference + frontier models around the globe. First stop: Singapore. Big congrats to all the builders at the GMI x @Zai_org Agent Hackathon in 🇸🇬 100+ on-site,
arXiv:2511.12968v2 Announce Type: replace Abstract: Concept erasure aims to remove harmful, inappropriate, or copyrighted content from text-to-image diffusion models while preserving non-target semant
arXiv:2604.10385v1 Announce Type: new Abstract: Generating complex multi-actor scenario videos remains difficult even for state-of-the-art neural generators, while evaluating them is hard due to the l
arXiv:2604.10095v1 Announce Type: new Abstract: With the emergence of 3D foundation models, there is growing interest in fine-tuning them for downstream tasks, where LoRA is the dominant fine-tuning p
🦔OpenAI is backing an Illinois state bill that would shield AI labs from liability in cases where their models cause mass casualties or large-scale financial disasters, defined as death or serious inj
arXiv:2604.11807v1 Announce Type: cross Abstract: The stable operation of autonomous off-grid photovoltaic systems dictates reliance on solar forecasting algorithms that respect atmospheric thermodyna
arXiv:2604.11496v1 Announce Type: cross Abstract: Dual-encoder Vision-Language Models (VLMs) such as CLIP are often characterized as bag-of-words systems due to their poor performance on compositional
This r/ollama community thread discusses practical strategies for managing context windows when using locally-run LLMs (via Ollama) for coding assistance on large codebases, where context limitations
arXiv:2604.11530v1 Announce Type: cross Abstract: Vision-Language Models (VLM) have revolutionized multimodal learning by jointly processing visual and textual information. Yet, they face significant
Microsoft silently raised prices on practically all of its Surface PCs by between 100 and 500 , with the last two models previously under 1,000 — the Surface Pro 12-inch and Surface Laptop 13-inch, wh
arXiv:2604.11351v1 Announce Type: new Abstract: Imitation learning is a powerful paradigm for training robotic policies, yet its performance is limited by compounding errors: minor policy inaccuracies
arXiv:2604.09063v1 Announce Type: cross Abstract: Human action recognition is pivotal in computer vision, with applications ranging from surveillance to human-robot interaction. Despite the effectiven
from my experience, even the best models (Opus 4.6, 5.4 xhigh / 5.3 codex) cannot write good code today without an amount of work that is equivalent to just doing the work myself am excited for a worl
This r/ollama community thread discusses methods that users employ to inject personal context — such as notes, documents, and preferences — into locally-run AI models via Ollama. Common approaches exp
arXiv:2603.13450v2 Announce Type: replace-cross Abstract: Discrete Diffusion Language Models have emerged as a compelling paradigm for unified multimodal generation, yet their deployment is hindered b
arXiv:2604.09544v1 Announce Type: cross Abstract: Large language models (LLMs) undergo alignment training to avoid harmful behaviors, yet the resulting safeguards remain brittle: jailbreaks routinely
arXiv:2604.09024v1 Announce Type: cross Abstract: Multi-modal large language models (MLLMs) have emerged as powerful tools for analyzing Internet-scale image data, offering significant benefits but al
arXiv:2604.09096v1 Announce Type: new Abstract: Image manipulation localization (IML) and general vision tasks are typically treated as two separate research directions due to the fundamental differen
deepagents is a harness / planning tool, filesystem backend, subagent spawning, memory management / thats the stack that matters / models are the cpu, the harness is the os / anyways, check it out htt
Only OG's know @NousResearch had bots back in 2024. This is when models were not capable. They've tried to solve this problem every way possible. Even @karan4d was exploring such ideas acitvely, @max_
A Reddit post on r/ollama showcasing a community-built, feature-rich macOS AI client designed for both local and cloud model access, including support for Ollama. The application emphasizes a modern,
This r/StableDiffusion thread discusses community recommendations for the highest-quality image generation models available. Flux 2 is widely regarded as arguably the best overall image generation mod
arXiv:2604.08545v1 Announce Type: new Abstract: The advent of agentic multimodal models has empowered systems to actively interact with external environments. However, current agents suffer from a pro
arXiv:2503.08292v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly applied to outpatient referral tasks across healthcare systems. However, there is a lack of stan
arXiv:2512.17489v2 Announce Type: replace Abstract: Text-to-image (T2I) models have demonstrated remarkable progress in creative image generation, yet they still lack precise control over scene illumi
arXiv:2604.08299v1 Announce Type: new Abstract: Chain-of-Thought (CoT) has become a cornerstone of reasoning in large language models, yet its effectiveness is constrained by the limited expressivenes
arXiv:2602.20231v2 Announce Type: replace-cross Abstract: Latent action representations learned from unlabeled videos have recently emerged as a promising paradigm for pretraining vision-language-acti
We had Lin on stage: 'the future is millions of models — one per application, one per use case.' Jet delivered a masterclass on reinforcement fine-tuning. Rob joined @WorkOS for some hot takes on the
The Sentence Transformers v5.4 update introduces first-class multimodal support, enabling the same familiar API to encode and compare texts, images, audio, and videos using both `SentenceTransforme...
Artificial intelligence model compression startup Refiant AI said today it has raised $5 million in seed funding from VoLo Earth Ventures to try to put an end to the “arms race” that has ignited a mul
Google's Gemma 4 31B is a dense multimodal model from Google DeepMind now available on Together AI's serverless infrastructure via the endpoint `google/gemma-4-31B-it`. It features a 256K context ...
Pelicans for Meta's new Muse Spark models - plus I did a bit of a deep dive into the Code Interpreter and fascinating 'container.visual_grounding' tools in their http://meta.ai chat UI https://simonwi
arXiv:2610.20840v1 Announce Type: cross Abstract: Robotic manipulation is inherently geometric, but what shape does the world take inside the policy that performs it? Prior work on vision-language-act
arXiv:2610.21195v1 Announce Type: new Abstract: On-policy distillation (OPD) improves a student language model by training on its own generated trajectories with supervision from a stronger teacher. H
arXiv:2610.21251v1 Announce Type: new Abstract: Vision-language-action (VLA) models are expected to follow instructions like their language backbones, yet prior work has focused on What-level instruct
arXiv:2610.22035v1 Announce Type: cross Abstract: Current heterogeneity-aware training systems for large models balance workloads by assigning unequal numbers of layers across pipeline stages, a strat
arXiv:2610.22146v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models present a promising paradigm for general-purpose robot manipulation, but closed-loop deployment is often limited by
arXiv:2610.20767v1 Announce Type: new Abstract: Can better feature discovery improve control over robot behavior through internal interventions and training data? Recent work in vision and language mo
arXiv:2610.21287v1 Announce Type: new Abstract: Training-free object removal commonly redirects self-attention away from the target region, but on few-step distilled diffusion models this often leaves
arXiv:2610.21160v1 Announce Type: new Abstract: Dual-system vision-language-action (VLA) models pair a high-frequency fast policy with a slow, expensive module, and published trigger mechanisms for in
arXiv:2610.19957v1 Announce Type: new Abstract: World action models (WAMs) jointly predict future visual states and robot actions, but processing dense future-frame tokens incurs substantial inference
arXiv:2610.17439v1 Announce Type: new Abstract: The success of autonomous research systems relies on the quality of the scientific hypotheses they generate. Recent studies report that human reviewers
arXiv:2610.17840v1 Announce Type: new Abstract: Multi-agent deliberation can improve recognition by criticizing and revising candidate answers, but fixed controls cannot respond to changes in disagree
arXiv:2610.19271v1 Announce Type: new Abstract: On-policy distillation provides dense supervision on the student's own samples, but its targets still come from the teacher. Verifier reinforcement lear
arXiv:2606.16569v2 Announce Type: replace Abstract: Registering two captures of the same indoor space taken at different times underpins persistent spatial memory for robots and AR systems, yet the re
arXiv:2610.15685v1 Announce Type: new Abstract: Conventional distillation transfers capability through teacher-generated demonstrations. LLM-as-a-Judge knowledge distillation offers a distinct and inc
arXiv:2601.12355v3 Announce Type: replace Abstract: To lower the expertise barrier in machine learning, the AutoML community has focused on the CASH problem, which jointly automates algorithm selectio
arXiv:2610.18596v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training improves robot foundation models (RFMs) beyond their demonstrations, but real-world deployment demands more:
arXiv:2610.17469v1 Announce Type: new Abstract: Social media platforms generate vast volumes of user-generated content that often obscure meaningful discourse, a phenomenon conceptualized as social no
arXiv:2610.14427v1 Announce Type: cross Abstract: As watermarking of LLM-generated text enters deployment, users increasingly need to check text whose source is unknown. Existing detectors read the wa
arXiv:2606.17192v2 Announce Type: replace Abstract: This paper develops constrained diffusion models with primal-dual inference (PDI) to sample from optimal distributions of entropy-regularized optimi