Knowledge catalogue
arXiv:2509.22887v2 Announce Type: replace Abstract: Theory of Mind (ToM)-an understanding of the mental states of others-is a key aspect of human social intelligence, yet, chatbots and LLM-based socia
arXiv:2510.01152v2 Announce Type: replace Abstract: LLMs cannot reliably recognize their parametric knowledge boundaries and often hallucinate answers to outside-of-boundary questions. In this paper,
arXiv:2604.10081v1 Announce Type: cross Abstract: Real-world image pairs often exhibit both severe degradations and large viewpoint changes, making image restoration and geometric matching mutually in
arXiv:2603.22241v2 Announce Type: replace Abstract: Diffusion Language Models (DLMs) offer attractive advantages over Auto-Regressive (AR) models, such as full-attention parallel decoding and flexible
arXiv:2505.09368v2 Announce Type: replace Abstract: Standard benchmarks for optical flow, scene flow, and stereo vision algorithms generally focus on model accuracy rather than robustness to image cor
arXiv:2505.17012v3 Announce Type: replace-cross Abstract: Existing evaluations of multimodal large language models (MLLMs) on spatial intelligence are typically fragmented and limited in scope. In thi
arXiv:2510.27484v2 Announce Type: replace-cross Abstract: Most work interpreting reasoning models studies only a single chain-of-thought (CoT), yet these models define distributions over many possible
arXiv:2604.11661v1 Announce Type: cross Abstract: Large language models (LLMs) have recently gained significant attention as a promising approach to accelerate scientific discovery. However, their app
arXiv:2511.05168v2 Announce Type: replace Abstract: Vision foundation models achieve strong performance on both global and locally dense downstream tasks. Pretrained on large images, the recent DINOv3
arXiv:2604.09391v1 Announce Type: cross Abstract: Machine unlearning poses challenges in removing mislabeled, contaminated, or problematic data from a pretrained model. Current unlearning approaches a
This r/ollama thread discusses user-reported issues with the Gemma 4 26B (a Mixture of Experts model) and its 'thinking' mode when used through Open WebUI. Key problems include the model getting stuck
arXiv:2604.08762v1 Announce Type: cross Abstract: Understanding instructional videos requires recognizing fine-grained actions and modeling their temporal relations, which remains challenging for curr
arXiv:2509.24250v3 Announce Type: replace Abstract: Teaching systems physical tasks is a long standing goal in HCI, yet most prior work has focused on non collaborative physical activities. Collaborat
This Reddit thread from r/StableDiffusion addresses the challenge faced by users in China trying to access and download models from Civitai, which may be restricted or slow due to network limitations
arXiv:2604.08987v1 Announce Type: new Abstract: As Large Language Models (LLMs) advance toward embodied AI agents operating in physical environments, a fundamental question emerges: can models trained
arXiv:2604.08958v1 Announce Type: cross Abstract: Reinforcement learning (RL) in robotics is often limited by the cost and risk of data collection, motivating experience transfer from a source task to
arXiv:2602.03604v3 Announce Type: replace-cross Abstract: We present EB-JEPA, an open-source library for learning representations and world models using Joint-Embedding Predictive Architectures (JEPAs
arXiv:2604.07017v1 Announce Type: new Abstract: AI assistants that interact with users over time need to interpret the user's current emotional state in order to respond appropriately and personally.
This is a ComfyUI automation workflow for the ACE-Step 1.5 XL music generation model that uses Qwen (a language model text encoder) to randomly generate music tags/captions without requiring LAMA, ...
arXiv:2603.13354v3 Announce Type: replace-cross Abstract: Reliable crop disease detection requires models that perform consistently across diverse acquisition conditions, yet existing evaluations ofte
arXiv:2604.08260v1 Announce Type: new Abstract: Knowledge Tracing (KT) aims to predict learners' future performance from past interactions. While recent KT approaches have improved via learning item r
arXiv:2604.06685v1 Announce Type: cross Abstract: While Vision-Language Models (VLMs) have demonstrated significant potential in chemical visual understanding, current models are predominantly optimiz
Anthropic announced **Claude Mythos Preview**, its most powerful AI model to date, which it is withholding from general public release due to its advanced and potentially dangerous cybersecurity ca...
arXiv:2604.06196v1 Announce Type: cross Abstract: Three-way logical question answering (QA) assigns True/False/Unknown to a hypothesis H given a premise set S. While modern large language models
arXiv:2510.04641v3 Announce Type: replace Abstract: Large-scale web-scraped text corpora used to train general-purpose AI models often contain harmful demographic-targeted social biases, creating a re
arXiv:2604.07413v1 Announce Type: new Abstract: The manufacturing sector is increasingly adopting Multimodal Large Language Models (MLLMs) to transition from simple perception to autonomous execution,
arXiv:2604.08131v1 Announce Type: new Abstract: The rapid spread of online misinformation has led to increasingly complex detection models, including large language models and hybrid architectures. Ho
arXiv:2603.01059v3 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have enabled increasingly capable chatbots. However, most existing systems focus on single-user sett
arXiv:2604.08192v1 Announce Type: cross Abstract: Reliable generalization metrics are fundamental to the evaluation of machine learning models. Especially in high-stakes applications where labeled tar
arXiv:2511.10354v1 Announce Type: cross Abstract: Cultural Heritage texts contain rich knowledge that is difficult to query systematically due to the challenges of converting unstructured discourse in
arXiv:2604.06950v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are increasingly being deployed as automated content moderators. Within this landscape, we uncover a critic
arXiv:2601.02535v2 Announce Type: replace Abstract: Selecting a single high-quality output from multiple stochastic generations remains a fundamental challenge for large language models (LLMs), partic
arXiv:2601.15356v4 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has empowered Multimodal Large Language Models (MLLMs) to achieve superior human preference alignment in Image Qua
arXiv:2604.06663v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to simulate social attitudes and behaviors, offering scalable 'silicon samples' that can approximat
arXiv:2604.06346v1 Announce Type: cross Abstract: Large language models have shown strong potential for Arabic medical text generation; however, traditional fine-tuning objectives treat all medical ca
arXiv:2010.00638v2 Announce Type: replace-cross Abstract: Generative models for tabular data have evolved rapidly beyond Generative Adversarial Networks (GANs). While GANs pioneered synthetic tabular
arXiv:2602.14819v2 Announce Type: replace Abstract: We present 'Testimole-conversational' a massive collection of discussion boards messages in the Italian language. The large size of the corpus, more
arXiv:2604.06906v1 Announce Type: cross Abstract: As Large Language Models reshape the global labor market, policymakers and workers need empirical data on which occupational skills may be most suscep
arXiv:2604.07267v1 Announce Type: cross Abstract: Gaussian process (GP) regression is a widely used non-parametric modeling tool, but its cubic complexity in the training size limits its use on mass
arXiv:2604.06264v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have enabled molecular reasoning for property prediction. However, toxicity arises from complex biolog
arXiv:2509.08016v2 Announce Type: replace Abstract: Video Large Language Models (VideoLLMs) face a critical bottleneck: increasing the number of input frames to capture fine-grained temporal detail le
arXiv:2603.18474v2 Announce Type: replace Abstract: Precise behavioral control of large language models (LLMs) is critical for complex applications. However, existing methods often incur high training
The *Interconnects.ai* article argues that fears around releasing an open-weight version of Claude Mythos are overstated, noting that closed frontier models still lead open-weight ones in robust, ...
Google released Gemma 4 on April 2, 2026 — a family of four open-weight models built on the same research as Gemini 3 and licensed under the permissive Apache 2.0 license, marking a significant shi...
Z.ai's GLM-5.1 is a 754-billion parameter open-weight Mixture-of-Experts model released on April 7, 2026 under an MIT license, designed as a post-training upgrade to GLM-5 with a focus on long-hori...
GLM-5.1 is now available through OpenCode Go, a low-cost subscription service ($5 first month, then $10/month) that provides access to open-source coding models with a zero data retention policy, m...
GLM-5.1: Towards Long-Horizon Tasks Chinese AI lab Z.ai's latest model is a giant 754B parameter 1.51TB (on Hugging Face) MIT-licensed monster - the same size as their previous GLM-5 release, and shar
A user on X (@willebrew) shared positive impressions of Cognition's SWE-1.6 Fast model, noting that a prototype UI it generated surpassed the output of Figma Make. SWE-1.6 is Cognition's latest mo...
Vercel’s unified API for hundreds of models — one endpoint, auth, failover, spend controls; pairs with the AI SDK and powers this wiki’s Ask models.
I understand this kind of product may not be exactly right for this subreddit, but I still think it deserves some attention, as it's an LLM frontend for local engines in the first place, and can be us
Reasoning From Scratch round 8, the finale! This last lecture in the series covers distillation as an efficient alternative to the previous reinforcement learning training runs. (Planning to take a br
arXiv:2610.22298v1 Announce Type: cross Abstract: Large language models (LLMs) can generate differential diagnoses for complex cases, but a useful second opinion must also be factually grounded, clini
arXiv:2610.20675v1 Announce Type: new Abstract: Agents pair reasoning models with harnesses that organize model calls, execute tools, load skill instructions, and retain history in memory. Understandi
arXiv:2610.21055v1 Announce Type: new Abstract: Recursive self-improvement, in which AI systems build stronger AI systems, is one promising route to superintelligence. We study a weaker form that can
tests : catch vanished rows in the fusion baseline (#30618) tests : update the Metal fusion baseline Re-record the MTL fusion baseline with the current build: 276 rows over 131 dummy models. Assisted-
arXiv:2610.21760v1 Announce Type: new Abstract: As image generation models become increasingly capable of producing highly realistic content, traditional forensic techniques are struggling to keep up.
arXiv:2607.18921v2 Announce Type: replace-cross Abstract: Circuit extraction identifies model components whose presence preserves a target behavior under ablation, but preserving behavior does not sin
arXiv:2610.21798v1 Announce Type: cross Abstract: Scaling robot manipulation models requires large amounts of interaction data, yet collecting diverse real-robot experience remains costly. Human manip
The real challenge of building an agentic system isn't the construction, it's the measurement. Evaluation engineering is a critical foundation for building reliable AI systems. Setting up systematic,
arXiv:2610.21498v1 Announce Type: new Abstract: Real-to-sim conversion aims to turn a captured video of a real environment into an editable 3D scene while preserving the geometry and layout of what wa