Knowledge catalogue
arXiv:2605.03371v1 Announce Type: new Abstract: Cross-scene hyperspectral image (HSI) classification stands as a fundamental research topic in remote sensing, with extensive applications spanning vari
arXiv:2605.03849v1 Announce Type: new Abstract: Distillation-based acceleration has become foundational for making autoregressive streaming video diffusion models practical, with distribution matching
arXiv:2605.02973v1 Announce Type: new Abstract: Modality translation is inherently under-constrained, as multiple cross-modal mappings may yield the same marginals. Recent work has shown that diffusio
arXiv:2605.02178v1 Announce Type: new Abstract: Recent progress in multi-turn reinforcement learning (RL) has significantly improved reasoning LLMs' performances on complex interactive tasks. Despite
arXiv:2605.01750v1 Announce Type: cross Abstract: Grounding is the collaborative process of establishing mutual belief sufficient for the current communicative purpose. While static grounding maps lan
arXiv:2605.03237v1 Announce Type: cross Abstract: Project-based learning improves student engagement and learning outcomes, yet allocating students to appropriately challenging projects while forming
arXiv:2605.02681v1 Announce Type: cross Abstract: We present two new classes of causal models of decision-making agents. Our approach is motivated by the needs of modeling the economics of computing s
arXiv:2605.01245v1 Announce Type: cross Abstract: Narrative archetypes (e.g., Hero's Journey, Three-act structure) provide universal story structures that resonate across cultures and media and are im
arXiv:2605.03838v1 Announce Type: new Abstract: We introduce TRACE, a cross-domain engineering framework for trustworthy agentic AI in operationally critical domains. TRACE combines a four-layer refer
arXiv:2605.03358v1 Announce Type: new Abstract: When orthodontists trace cephalometric radiographs, they follow a structured workflow: identify the soft tissue profile, partition the skull into anatom
truly scary: anybody, no matter how noble, can be destroyed by misused AI. Artificial intelligence can create deceptive videos that rapidly damage a politician's public reputation. A new study reveals
arXiv:2605.02640v1 Announce Type: new Abstract: As artificial intelligence (AI), including machine learning (ML) models and foundation models (FMs), is increasingly deployed in high-stakes domains, en
arXiv:2605.01257v1 Announce Type: new Abstract: Large-scale GPS trajectory data offer rich observations of human mobility, yet assigning trip purposes to detected stops remains challenging due to the
arXiv:2502.04419v3 Announce Type: replace-cross Abstract: Generating synthetic datasets via large language models (LLMs) has emerged as a promising approach to improve LLM performance. However, LLMs i
arXiv:2605.03517v1 Announce Type: new Abstract: Self-supervised learning (SSL) excels at finding general-purpose latent representations from complex data, yet lacks a unifying theoretical framework th
arXiv:2605.03677v1 Announce Type: new Abstract: On-policy distillation (OPD) has recently emerged as an effective post-training paradigm for consolidating the capabilities of specialized expert models
What’s going on in semis is not sustainable per GS Everyone spending on AI is losing money except for semiconductor companies and the dynamic is “unprecedented and unsustainable” “Something has to cha
arXiv:2605.03314v1 Announce Type: new Abstract: In single-stream autoregressive interfaces, the same tokens both update the model state and constitute an irreversible public commitment. This coupling
arXiv:2605.03304v1 Announce Type: new Abstract: The European Union's Carbon Border Adjustment Mechanism (CBAM) creates a complex challenge for the interconnected European electricity market. Tradition
yep, we are about to live in a world where nobody trusts anything. just like Putin always wanted. congratulations! ps it will suck @GaryMarcus Or very soon no one will take any photo or video seriousl
arXiv:2605.01336v1 Announce Type: new Abstract: News outlets shape public opinion at a scale that makes automated detection of political bias and factuality essential. However, the field still lacks u
arXiv:2605.01232v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled visually realistic demonstration generation from a single expert trajectory and a short mul
arXiv:2605.01034v1 Announce Type: new Abstract: As large language models grow increasingly capable, concerns about their safe deployment have intensified. While numerous alignment strategies aim to re
arXiv:2605.01172v1 Announce Type: new Abstract: We present a non-asymptotic theory of generalization in deep learning where the empirical neural tangent kernel partitions the output space. In directio
arXiv:2511.18088v2 Announce Type: replace Abstract: Tendon-driven continuum robots offer intrinsically safe and contact-rich interactions owing to their kinematic redundancy and structural compliance.
arXiv:2605.00838v1 Announce Type: cross Abstract: In mobile telecommunications, alarms act as early warning signals. They are triggered when a cell, the basic unit of radio coverage, shuts down or beh
arXiv:2505.08392v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting trades inference speed for reasoning accuracy. Existing compressors force a compromise as static gradient technique
arXiv:2605.02742v1 Announce Type: cross Abstract: Motion in-betweening is one of the most artistically demanding and time consuming stages of 3D animation, where the expressivity and rhythm of motion
arXiv:2605.01642v1 Announce Type: new Abstract: Prevailing alignment methods target a fixed set of preferences and therefore risk forcing value lock-in as societal norms evolve over time. We introduce
arXiv:2605.01778v1 Announce Type: new Abstract: Adversarial imitation learning (AIL), a prominent approach in imitation learning, has achieved significant practical success powered by neural network a
arXiv:2511.21678v2 Announce Type: replace-cross Abstract: MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo -- solving each problem independently and often repeating the sam
arXiv:2605.01643v1 Announce Type: new Abstract: We study AI alignment through the lens of law-and-economics models of deterrence and enforcement. In these models, misconduct is not treated as an exter
AI music generator Udio just admitted in a court filing that it trained on audio scraped from YouTube videos. It’s already being sued by labels & artists for what they say is copyright infringement on
Alex Karp now sounding like @garymarcus. Sooner or later, everyone figures it out. Palantir CEO Alex Karp goes after AI slop. The fight over AI “slop” is really a fight over whether software is perfor
arXiv:2509.09723v3 Announce Type: replace Abstract: Psychological measurement is critical to many disciplines. Despite advances in measurement, building nomological networks, theoretical maps of how c
arXiv:2605.02320v1 Announce Type: cross Abstract: Proximal Policy Optimization (PPO) dominates deep RL but faces a fundamental dilemma. Its 'hard clipping' mechanism discards valuable gradient informa
arXiv:2605.02439v1 Announce Type: new Abstract: Synthesizing realistic and diverse anomalous samples from limited data is vital for robust model generalization. However, existing methods struggle to r
arXiv:2605.01772v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for embodied intelligence, enabling robots to perform tasks based on natural l
arXiv:2605.02200v1 Announce Type: new Abstract: Online advertising governance faces significant challenges due to the non-stationary nature of regulatory policies, where emerging mandates (e.g., restr
arXiv:2601.18569v2 Announce Type: replace-cross Abstract: In this letter, we propose an Attention-Based Neural-Augmented Kalman Filter (AttenNKF) for state estimation in legged robots. Foot slip is a
arXiv:2605.01229v1 Announce Type: cross Abstract: Cross-attention patterns in neural machine translation (NMT) are widely used to study how multilingual models align linguistic structure. We report a
arXiv:2605.01295v1 Announce Type: new Abstract: In the pursuit of autonomous learning systems, the foundational assumption of stationarity, the premise that data distributions and model behaviors rema
arXiv:2605.01901v1 Announce Type: new Abstract: Traffic digital twins are powerful tools for advanced traffic management, and most systems are built on static geometric representations. However, these
arXiv:2605.01324v1 Announce Type: new Abstract: Although reinforcement learning (RL) has significantly advanced reasoning capabilities in large multimodal language models (MLLMs), its efficacy remains
arXiv:2605.02528v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) navigation policies often overfit to the structure of their training environments, as environmental diversity is typ
arXiv:2605.01289v1 Announce Type: new Abstract: This paper investigates goal-directed tracking control of underactuated blimps with center-of-mass (CoM) reconfiguration. Unlike conventional overactuat
arXiv:2605.02375v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard approach for improving reasoning in language models, yet models trained with
arXiv:2605.02745v1 Announce Type: new Abstract: Molecular property models increasingly support high-stakes drug-discovery decisions, but their outputs are often difficult to audit: classical predictor
🚨 BOTH ALTMAN AND BROCKMAN SELF-DEALING ON CEREBRAS >Greg Brockman acquires personal Cerebras ownership in 2017 >Altman, separately, invests in Cerebras >Brockman pushes OpenAI to merge with Cerebras
arXiv:2605.01242v1 Announce Type: new Abstract: Reinforcement learning (RL) is a fundamental framework for sequential decision-making, in which an agent learns an optimal policy through interactions w
arXiv:2605.02103v1 Announce Type: new Abstract: The analysis of Temporal Difference (TD) learning in the average-reward setting faces notable theoretical difficulties because the Bellman operator is n
arXiv:2605.02043v1 Announce Type: new Abstract: Asynchronous stochastic gradient descent (SGD) enables scalable distributed training but suffers from gradient staleness. Existing mitigation strategies
Brockman confirms that Sam was fired for not being consistently candid. Crazy that @karaswisher blocked me for saying that the board fired Sam for not being consistently candid, when that is in fact w
Brockman’s counsel is doing a good job of laying out the timeline — but done little so far to refute yesterday’s dissection of her client’s self-dealing and dodgy behavior regarding his fiduciary resp
arXiv:2605.01330v1 Announce Type: new Abstract: Low-bit quantization is a practical route for efficiently deploying vision Transformers, yet activation outliers complicate fully quantized deployment.
arXiv:2605.02159v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) has delivered strong results in domains such as Atari and Go, but it still suffers from high sample cost and weak tran
arXiv:2605.01048v1 Announce Type: new Abstract: Counterfactual prompting (i.e., perturbing a single factor and measuring output change) is widely used to evaluate things like LLM bias and CoT faithful
arXiv:2605.00071v1 Announce Type: cross Abstract: Agentic payment systems extend delegated action to financial transfers, but scaling them on stablecoin rails in regulated settings requires safeguards
arXiv:2505.19607v2 Announce Type: replace Abstract: Test-time adaptation (TTA) enhances model robustness by enabling adaptation to target distributions that differ from training distributions, improvi
arXiv:2605.01309v1 Announce Type: new Abstract: Long-tailed distributions are common in real-world recognition tasks, where a few head classes have many samples while most tail classes have very few.