Knowledge catalogue
arXiv:2607.22313v1 Announce Type: cross Abstract: Estimating contemporaneous bidirectional interactions from observational data is difficult because each outcome is endogenous to the other, while flex
arXiv:2607.21648v1 Announce Type: new Abstract: The human-like morphology of humanoid robots grants them exceptional potential for agile and versatile motor capabilities, but it also introduces signif
arXiv:2607.22166v1 Announce Type: new Abstract: Path planning under partial observability remains challenging because an agent must make long-horizon navigation decisions from only locally bounded obs
arXiv:2607.21953v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) communication is expected to support a wide range of low-altitude applications in 6G mobile networks. However, traditional
arXiv:2607.21978v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures have been widely adopted in large language models, yet parameter-efficient fine-tuning (PEFT) for MoE models rema
arXiv:2606.18681v2 Announce Type: replace Abstract: Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational overhead due to the large number of visual token
arXiv:2607.21671v1 Announce Type: new Abstract: Neural network compression and interpretability remain open challenges in modern deep learn- ing, where billion-parameter architectures deliver impressi
Nice little insights on doing autoresearch with coding agents. Hand a coding agent a dataset, an eval script, one editable file, and no supervision. That's autoresearch and it tries to optimize the nu
arXiv:2607.22226v1 Announce Type: new Abstract: Foundation-model-based vision-language navigation (VLN) has advanced autonomous robot navigation by enabling robots to interpret natural-language instru
arXiv:2607.21756v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in database-backed applications to classify tuples, filter records using semantic predicates, extra
arXiv:2607.22098v1 Announce Type: cross Abstract: Large reasoning models (LRMs) generate long reasoning traces before producing final answers. While these traces may contain useful signals for halluci
arXiv:2607.22413v1 Announce Type: cross Abstract: Sample retrieval tools can help composers find harmonically compatible material, but querying from a fixed reference sample becomes less informative a
arXiv:2607.22225v1 Announce Type: new Abstract: Safe autonomous navigation in shared environments requires the ability to anticipate and react to the latent behaviors of surrounding robots. In this pa
arXiv:2512.23849v2 Announce Type: replace-cross Abstract: Sophisticated attackers can evade detection-based security by using encryption, stealth tactics, and low-rate attack patterns. This challenge
arXiv:2607.21843v1 Announce Type: cross Abstract: Empirical Bayes (EB) performs simultaneous inference across many related latent variables. Classical EB assumes that the likelihood p(x | z) is tracta
arXiv:2505.24849v2 Announce Type: replace-cross Abstract: For three decades statistical mechanics has been providing a framework to analyse neural networks. However, the theoretically tractable models
arXiv:2509.22352v3 Announce Type: replace Abstract: Survival analysis is a cornerstone of clinical research by modeling time-to-event outcomes such as metastasis, disease relapse, or patient death. Un
arXiv:2607.22345v1 Announce Type: new Abstract: Generative social robots (GSRs) powered by large language models offer new possibilities for personalized tutoring in higher education, but also introdu
arXiv:2512.15423v2 Announce Type: replace Abstract: Monocular depth foundation models achieve remarkable generalization by learning large-scale semantic priors, but this creates a critical vulnerabili
arXiv:2607.21635v1 Announce Type: new Abstract: Personal agents maintain memories, learned skills, tool configurations, and policy state that evolve with each user. Existing agent benchmarks often eva
arXiv:2607.21887v1 Announce Type: cross Abstract: Foreign language anxiety (FLA) can be a major barrier to second language acquisition (SLA), especially in conversational contexts. With the proliferat
arXiv:2607.21985v1 Announce Type: cross Abstract: The increasing deployment of large language models (LLMs) has magnified the computational and memory bottlenecks of autoregressive decoding, where low
GigaChat Audio 10B is an audio-native LLM built on top of the GigaChat 3.1 Lightning text model. A Conformer speech encoder and a modality adapter feed audio embeddings directly into a Mixture-of-Expe
TL;DR llama.cpp fork with more KV cache quantization features, with all claims supported by benchmarks: KVarN, KV cache precision tail, additional types of standard KV cache (q2_0-q3_1, q6_0, q6_1), a
New research from NVIDIA. Does AdamW have a scale ceiling? This work claims yes, and shows where it sits. At batch sizes up to 100M tokens for next-token prediction, SOAP and Muon maintain training st
I have been running some experiments with smaller open-weight LLMs on multiple-choice questions of Swedish medical licensing exams. On a dataset called MedQA-SWE, GPT-4 scored 84% accuracy in 2024 and
--> .abbel-fig { display: block; text-align: center; margin: 2.4em 0; line-height: 1.4; max-width: 100%; } .abbel-fig img { display: block; margin: 0.65em auto 0; height: auto; max-width: 100%; } /* I
A little over a year ago I got frustrated trying to fine-tune SDXL on my RTX 3060. Every option either forced lower resolution, locked away important settings behind massive config files, or needed a
arXiv:2501.06857v3 Announce Type: replace Abstract: Perhaps the most popular modern formulation of actual causality is the HP account by Halpern and Pearl. Recent advancement has focused on extension
arXiv:2607.20700v1 Announce Type: cross Abstract: The operation of blockchain is governed by consensus algorithms (CA). Several consensus mechanisms require significant computational power, while othe
arXiv:2607.21094v1 Announce Type: new Abstract: We study feature-level and node-level explanations for graph neural networks (GNNs) through the lens of Aumann-Shapley attribution. Path-integral method
arXiv:2607.21043v1 Announce Type: new Abstract: Safe and efficient navigation in mixed-traffic environments remains a critical challenge for Autonomous Vehicles (AVs), primarily due to the complex int
arXiv:2607.20748v1 Announce Type: cross Abstract: Impact hammers, also known as rock-breakers, are essential machines in mining operations, where they perform secondary reduction. In underground minin
arXiv:2607.21057v1 Announce Type: new Abstract: Text-based person retrieval faces a critical but under-explored challenge: the inherent uncertainty of query granularity in real-world scenarios. This p
// Agentic Context Management // Great read for the weekend. (bookmark it) Production agents fail less on reasoning and more on what sits in their context. Conversation history, big prompts, huge tool
AI Engineer Paris is back! After an incredible first edition, we’re excited to announce AI Engineer Paris 2026, this time hosted by our friends at @MistralAI. 🎤 CFP is open. Submit your talk by July 3
arXiv:2607.20452v1 Announce Type: new Abstract: Modern software quality assurance demands intelligent, autonomous systems capable of adaptive decision-making across distributed cloud environments. Thi
arXiv:2607.20498v1 Announce Type: new Abstract: Large language models (LLMs) augmented with tools are emerging as autonomous agents capable of using Web engine, APIs, and code to solve complex, long-h
arXiv:2607.20902v1 Announce Type: cross Abstract: Goal reasoning in Non-Axiomatic Logic (NAL) explains how an adaptive system derives means for realizing desired events under insufficient knowledge an
arXiv:2607.20525v1 Announce Type: new Abstract: OpenAI's recent disproof of the Erdos unit distance conjecture marked a milestone for AI in mathematics. It also inspired another breakthrough: a human
arXiv:2601.07556v2 Announce Type: replace-cross Abstract: Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) face significant deployment challenges due to inter-subject variability, sig
arXiv:2607.20981v1 Announce Type: new Abstract: Efficient multimodal inference is increasingly constrained not only by model quality or FLOP count, but also by the cost of preserving, moving, routing,
arXiv:2607.20434v1 Announce Type: cross Abstract: As the parameter size of language models continues to grow, effective model compression is required to reduce their computational and memory overhead.
arXiv:2607.20461v1 Announce Type: cross Abstract: Present implementations of artificial intelligence (AI) ethics do not adequately take feelings, or affect, into account. If AI should be aligned with
arXiv:2607.21196v1 Announce Type: cross Abstract: Ninety-Nine Prolog Problems (P-99) is a famous set of Prolog exercises. We solved the first thirty three just by prompting an LLM (Large Language Mode
arXiv:2607.21125v1 Announce Type: new Abstract: Image restoration agents have recently emerged as a flexible paradigm for handling diverse and unpredictable degradations in real-world scenarios. Exist
arXiv:2607.20530v1 Announce Type: cross Abstract: Semi-supervised anomaly detection plays a key role in diverse fields such as process monitoring, healthcare, and finance. However, lightweight methods
arXiv:2607.20444v1 Announce Type: cross Abstract: Large language models (LLMs) can produce deceptive responses: outputs that mislead users in service of a contextually or experimentally induced goal.
arXiv:2607.20490v1 Announce Type: new Abstract: Edge Intelligence has emerged as a key paradigm for enabling real-time applications in smart cities by shifting computation from centralized cloud data
arXiv:2509.03922v2 Announce Type: replace Abstract: Multiview video is a key format for 3D applications such as free-viewpoint broadcasting and virtual reality, yet its large data volume poses signifi
arXiv:2607.21458v1 Announce Type: new Abstract: The rise of human-AI collaborative writing has created a growing need for fine-grained detection methods that support localizing likely LLM-generated co
arXiv:2607.20900v1 Announce Type: new Abstract: With the increasing diversity of spoofing attacks, there is a growing demand for unified Face Anti-Spoofing (FAS) models capable of detecting both physi
arXiv:2607.20446v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly used by students to generate natural language responses and program code, there is growing interest in
arXiv:2607.20820v1 Announce Type: new Abstract: Body-based emotion recognition is important for real-time affective systems, but graph-based skeleton models can be computationally expensive. This pape
arXiv:2607.21529v1 Announce Type: cross Abstract: Test-Time Tuning (TTT) on pretrained diffusion models has emerged as a powerful paradigm for video editing. However, there exists a foundational misma
arXiv:2607.20480v1 Announce Type: new Abstract: Accurate distribution system topology is essential for outage localization, voltage analytics, and operation of distribution grids, yet maintaining reli
arXiv:2607.21412v1 Announce Type: new Abstract: Large Language Models (LLMs) excel at natural language understanding and generation but remain unreliable for multi-step logical reasoning, especially i
arXiv:2607.20527v1 Announce Type: new Abstract: Agentic LLM systems such as OpenScholar and PaperQA2 read the scientific literature and return cited answers, and both they and their benchmarks already
arXiv:2607.21210v1 Announce Type: cross Abstract: Existing approaches to multi-agent belief combination have established mature foundations for combining uncertain beliefs under common assumptions: co
arXiv:2607.21184v1 Announce Type: new Abstract: Inductive Logic Programming (ILP) originated within the Logic Programming community in the Nineties as a framework for combining symbolic learning with