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Thursday 15 October
- PaperWhat Social Media Teaches Us About Accumulative AI Risks
Prominent AI safety discussions emphasize existential threats and catastrophic events, such as AI-enabled nuclear conflict or engineered biological outbreaks. This positi
- PaperTriSAR-3D and PaintFusion: A Novel Trimodal LiDAR-RGB-Thermal Dataset and Method for 3D Person Detection in Search and Rescue
Reliable 3D person detection is important for rescue robotics to give first responders situational awareness. Yet most multimodal 3D detection research targets automotive
- PaperRealCLI: Toward a Unified Evaluation of Human-Agent Collaboration for CLI Agents
Command-line interface (CLI) agents increasingly execute longer-horizon tasks, yet existing benchmarks either assume that user instructions remain fixed throughout execut
- PaperKFS$^4$LAM: Adaptive KeyFrame Selection with Structure-Aware Mapping for Endoscopic Gaussian Splatting SLAM
Gaussian-splatting Simultaneous Localization and Mapping (SLAM) augments conventional SLAM with a dense, renderable 3D scene representation, enabling high-quality reconst
- PaperJAVIS: Joint Audio-Visual Interaction and Streaming for Real-Time Conversational Agents
Human communication is inherently multimodal, conveying intent not only through linguistic and vocal cues but also through visual signals. However, existing conversationa
- PaperGenerative Value Classifier
Q-learning is premised on learning a function to predict the value of a state-action pair, with the goal of using such a function to guide policy improvement. Most approa
- PaperUpper bounds on the number of causal pieces in spiking neural networks
The input space of single-spike neural networks decomposes into causal pieces, and the number of causal pieces has been shown to provide a lower bound on the approximatio
- PaperStar Light, Star Bright: Can Multimodal Models Parse an Astronomy Visual Question Answering Dataset Right?
Figures are essential for scientific communication, and the field of Visual Question Answering (VQA) aims to test the figure understanding capabilities of large multimoda
- PaperA Unified Theory of Image Scaling: Point Spread Functions, Discrete Kernels, and Scale-Spaces
We derive the optically aligned system of image-scaling operators $\mathbf{K}_s$ that reproduces optical zoom (exact zoom-out, canonical zoom-in), by identifying a Huygen
- PaperHas GPT-6-Astra Achieved Embodied Intelligence?
GPT-6-Astra demonstrates a level of competence in robotic manipulation and navigation that challenges the conventional paradigm of building specialized models for individ
- PaperLIBERO-PeRM: Benchmarking Personalized Robotic Manipulation
Personalization is essential for general-purpose robots to transition into household environments and achieve true practicality. While general robotic manipulation has be
- PaperGen4P: Video Generators are 4D Perceivers
We introduce Gen4P, a unified framework for recovering 4D geometry and motion from monocular video. We show that a pretrained video generator can be repurposed into a fee
- PaperWhich Tokens to Merge? Diffusion Dynamics for Efficient Image Generation
Token merging has emerged as an effective training-free strategy for accelerating diffusion models by reducing redundant token computation while minimizing generation deg
- PaperSoftCache: Adaptive Step Size Caching for Diffusion Transformers
Diffusion and flow models generate a sample over iterative steps, each a full pass through a large network, and that pass dominates generation cost. Training-free caching
- PaperDiscovering state-of-the-art quantum circuits with large language models
Significant efforts are currently being directed toward the implementation of large-scale quantum information processors, but realizing useful quantum advantage also requ
- PaperT2-z: Test-Time Optimization of Environment Latents for Robotic World Models
Predicting how the world responds to an action requires more than what can be seen: robots must account for environmental factors that are neither directly observable nor
- PaperPerceive, Predict, and Plan: a Unified World Action Model for Egocentric Dexterous Manipulation
We introduce P$^{3}$-WAM, a unified world action model for egocentric dexterous manipulation that learns 3D perception, action-conditioned prediction, and goal-directed p
- PaperCoDA: Co-Evolution of Data Engines and Action Policies
Generative simulation can automate robot environment construction, but physically valid environments are not necessarily useful for training. The challenge is to identify
- PaperGrounding Generative Verification in 3D Content
Recent advances in multimodal large language models (MLLMs) and 3D generation have expanded 3D understanding and synthesis. However, beyond visual fidelity, task-specific
- PaperPathFM: Fast Generative Forecasting of Multivariate Trajectories
Time series foundation models are becoming increasingly popular for general-purpose forecasting. However, most leading models predict marginal quantiles, leaving the depe
- PaperPACE: Pareto-Adaptive Compression for Efficient Native MLLMs
Native multimodal large language models (native MLLMs) jointly encode visual and linguistic sequences within a unified autoregressive Transformer, emerging as a promising
- PaperDK-VLM: Geometry as Position for Spatial Reasoning in Vision-Language Models
Vision-language models still struggle to understand 3D spatial relations across views and update spatial judgments as the observer moves. A common approach fuses 3D recon
- PaperOmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling
Generative visual verifiers play a crucial role in advancing multimodal intelligence. To enhance the robustness of visual verifiers in complex multimodal scenarios involv
- PaperRethinking Routing Exploration in Modern Mixture-of-Experts
Mixture-of-experts (MoE) models have become an important approach for scaling model parameters. Modern MoE architectures increasingly combine two design choices: fine-gra
- PaperSUPRA-TEX: 3D Generation with Super-Aligned Texture
Single image 3D generation aims to dress a given 3D mesh with relightable materials while faithfully preserving the visual details of a reference image. Existing methods
- PaperFDE-Gym: The Last Mile of AI Delivery
Existing agent benchmarks typically evaluate agents on well-specified tasks defined by issue reports, specifications, or task tickets. Real-world customer delivery is dif
- PaperSpeculative Forcing for Efficient Autoregressive Video Generation
Few-step autoregressive video generators enable streaming generation, yet they run every token through the final denoising step, regardless of how much refinement it need
- PaperMLExpert: Towards a Generalist Agentic Model for Autonomous Machine Learning Engineering
Large language models (LLMs) are expanding from assisting scientific research and engineering to autonomously developing and improving AI systems, advancing AI for AI (AI
- PaperGeoState: Learning View-Decoupled Geometry States for 3D World Modeling
Recent 3D world models increasingly use features from geometry foundation models (GFMs) as predictive world states, benefiting from their rich geometric priors. However,
- Paper3DCodeVerse: Exploring 3D Worlds as Code
We introduce 3DCodeVerse, a research ecosystem that enables coding agents to create editable and verifiable 3D content at scale. 3DCodeVerse comprises large-scale, high-q
- PaperDexterity from Supervised Play
How can robots autonomously collect the contact-rich experience needed to learn dexterous manipulation? We present DSP: Dexterity from supervised play, a framework in whi
- PaperLean Graph Search for Formal Theorem Proving
Retrieving relevant lemmas is crucial for formal theorem proving, enabling provers to build machine-checkable proofs from established mathematical results. Recent retriev
- PaperRobust Reinforcement Learning for Dynamic Treatment Regimes under Model and Measurement Uncertainty
We develop a robust reinforcement learning (RL) framework for learning adaptive treatment policies that generalize across patients and remain reliable under errors in the
- PaperEvaluation Awareness Beyond English: Do LLMs Act Differently When Tested in Indic Languages?
Large language models (LLMs) can often tell when they are being tested. This ability, known as evaluation awareness, can lead models to act more cautiously during safety
- PaperKnowGPO: Knowledge-Grouped Policy Optimization for Search Agents
Deep search agents solve knowledge-intensive tasks through long-horizon, multi-turn interactions, where assigning credit to individual search decisions is fundamentally d
- PaperDesigning Transformers for Continuous Diffusion Language Models
Continuous diffusion language models (CDLMs) offer an alternative approach to parallel language generation; however, most existing studies directly use transformer archit
- PaperACEdit: Stable Multi-Turn Image Editing via Asymmetric Conditioning
Image editing models produce impressive results for individual edits, but their quality often deteriorates over multiple editing turns. Each editing turn introduces small
- PaperTwice Upon a Time: Complementary Representations for Time-Series Reasoning
Time Series Language Models (TSLMs) enable language-based understanding and reasoning over temporal data, yet a fundamental question remains: what information should thei
- PaperDense4D: Pixel-Level 4D Human Correspondence
Reconstructing human motion in 4D requires identifying the same surface points through articulation, deformation and changes in visibility. We introduce Dense4D, to our k
- PaperTraining Reasoning Models to Generate Diverse Scientific Ideas
One of the first steps of a research pipeline is generating ideas. Large Language Models (LLMs) are increasingly used to automate this step, but most of this work optimiz
Headlines and links come from the labs' own blogs, Hacker News and the GDELT news index, and from the sources our index already follows. We show a short excerpt and always link to the original. A launch reported by a news site rather than the lab is marked “Reported” until the lab itself announces it.