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169,051 papers · 148 categories

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15304560 · May 202619922001200920182026
48 results for grid probing

Designing probing injections for smart inverters to infer non-metered loads.

problem Inferring non-metered loads from electric grid probing.
method Designing probing injections that adhere to inverter and network constraints, using a library of candidate vectors and SDP relaxation for noisy data.
result Improved load estimates through optimal probing design.

Study finds optimal learning rate schedules for sub-100M quantization-aware training across bit-widths.

problem Optimal learning rate schedules for quantization-aware training depend on bit-width.
method Factorial grid testing over bit-width, warmdown fraction, LR magnitude, model size, and seed.
result INT6 QAT requires a different schedule than higher-precision training, falsifying the primary hypothesis.

Machine learning improves probing of quantum systems via synchronization.

problem Characterizing the dissipation features of quantum systems.
method Machine learning applied to a probing scheme with quantum synchronization.
result Machine learning significantly improves the inference of dissipation features from probe observables.

We identify spectral conditions for reliable neural probe interpretation.

problem Unreliable performance of linear probes in interpreting neural representations.
method Formalized Spectral Identifiability Principle (SIP) based on eigengap and Fisher error.
result Reliability of neural probes depends on the eigengap relative to Fisher estimation error.

Paper introduces Manifold Probe for discovering representation manifolds in superposition.

problem Discovering representation manifolds in complex superposition representations.
method Generalizes linear regression probes to learn feature spaces and directions in superposition representations.
result Demonstrates Manifold Probe on Llama 2-7b representations, finding causally involved manifolds in model behaviour.

OLPA optimizes online user-centric selection with probing, achieving near-optimal regret bounds.

problem Sequential decision-making with unknown resources and rewards.
method Probing-augmented user-centric selection (PUCS) framework, greedy probing algorithm, OLPA algorithm.
result OLPA achieves a near-optimal regret bound of O(T+ln2T)\mathcal{O}(\sqrt{T} + \ln^{2} T) for online settings.

This paper explores what causal structures can be distinguished by observational and interventional probing schemes.

problem Identifying causal structures with latent variables using observational and interventional data.
method Investigates the power of different probing schemes (observation vs. intervention) to distinguish causal structures.
result Two causal structures are indistinguishable if they share the same mDAG structure.

Interactive agent modeling by learning to probe improves understanding of other agents' behaviors.

problem Understanding and predicting the behaviors of other agents in interactive scenarios.
method An interactive agent modeling scheme enabled by encouraging the agent to learn to probe, combining imitation learning and curiosity-driven reinforcement learning.
result The agent model learned by the proposed approach generalizes better and enhances performance in multiple applications.

Paper analyzes why deeper layers of ViTs perform worse on out-of-distribution tasks.

problem Performance degradation of intermediate layers in ViTs under distribution shift.
method Extensive linear probing experiments across various benchmarks and fine-grained analysis of transformer modules.
result Probing feedforward network activations yields best performance under significant distribution shift.

CwA optimizes search performance by jointly learning a balanced database partition and a neural probing function.

problem Suboptimal search performance due to mismatched database and query distributions.
method CwA jointly learns a balanced database partition and a neural probing function to optimize search performance directly for the query distribution.
result CwA achieves up to 4.7x throughput over state-of-the-art methods at equal recall.

Study examines flaws in probing LLMs' knowledge and introduces a new method.

problem Flaws in existing methods for probing the veracity of LLMs' internal knowledge.
method sAwMIL (Sparse-Aware Multiple-Instance Learning) combining multiple-instance learning with conformal prediction.
result LLMs encode a third type of signal distinct from true and false.

We study the statistical behavior of reasoning probes in a stylized model of iterative computation inspired by neural algorithmic reasoning. The underlying computation is given by a looped Boolean circuit whose graph is a perfect νν-ary tree (ν2ν\ge 2), with outputs recursively fed back as inputs across computation ro…

2026-02-03abs ↗pdf ↗

Improved unsupervised probing for ranking tasks using Contrast-Consistent Ranking.

problem Improving self-consistency in language model rankings.
method Adapting Contrast-Consistent Search (CCS) to Contrast-Consistent Ranking (CCR) for ranking tasks.
result CCR probing outperforms prompting techniques across different models and datasets.

This research discovers model architecture and training dataset characteristics through strategic input probing.

problem Discovering model architecture and training dataset characteristics in black box models.
method Structured input probes and model outputs are used to train a deep classifier for image and text classification.
result The approach successfully distinguishes between different image and text datasets and architectures.

We present a grid diagram analogue of Carter, Rieger and Saito's smooth movie theorem. Specifically, we give definitions for grid movies, grid movie isotopies and present a definition of grid planar isotopy as a particular subset of the grid diagram moves: stabilization, destabilization and commutation. We show that gr…

2013-03-07abs ↗pdf ↗

Researchers create holographic super-embeddings for M5 and M2 branes.

problem No concrete examples of super-embeddings for M5 and M2 branes existed.
method Constructed explicit holographic super-embeddings of probe M5 and M2 branes into their super-AdS backgrounds.
result Explicit holographic super-embeddings of M5 and M2 branes were successfully constructed.

The paper introduces triple grid diagrams to construct Lagrangian surfaces in complex projective space.

problem Constructing Lagrangian surfaces in complex projective space.
method Defining and analyzing triple grid diagrams to determine Lagrangian caps and surfaces.
result Triple grid diagrams can determine closed Lagrangian surfaces in CP2\mathbb{CP}^2 under certain conditions.

Half grid diagrams prove every link can be represented by a special type of grid diagram.

problem Representing links using grid diagrams and related invariants.
method Defining half grid diagrams and constructing canonical pairs, proving equivalence to Jones' construction, relating to classical link invariants.
result Established a new method to relate the oriented Thompson index to classical link invariants and provided bounds for knot invariants.

New method tightens federated probe-logit distillation rates under varying bandwidths.

problem Estimating conditional distributions in federated learning with heterogeneous bandwidth constraints.
method Developed a new federated probe-logit distillation (FPLD) method with optimal allocation for varying bandwidths.
result Achieved matching lower and upper bounds for the minimax rate under heterogeneous bandwidths.

We study supersymmetric probe M5-branes in the AdS_4 solution that arises from M5-branes wrapped on a hyperbolic 3-manifold M_3. This amounts to introducing internal defects within the framework of the 3d-3d correspondence. The BPS condition for a probe M5-brane extending along all of AdS_4 requires it to wrap a surfac…

2014-07-01abs ↗pdf ↗

Grid homology properties for MOY graphs studied.

problem Defining and studying properties of grid homology for MOY graphs.
method Defined grid homology from Harvey and O'Donnol's work. Studied properties using oriented skein relation, edge contraction, and parallel edge unification.
result Properties of grid homology for MOY graphs were studied and defined.

New method constructs moduli spaces of Lagrangian surfaces in CP^2 from grid diagrams.

problem Constructing explicit examples of triple grid diagrams for Lagrangian surfaces in CP^2.
method Elegant geometric construction reducing to linear algebra.
result Explicit construction of moduli space of triple grid diagrams.

PROBE algorithm efficiently solves sparse high-dimensional linear regression.

problem Sparse high-dimensional linear regression models with complex parameter spaces.
method Partitioned empirical Bayes ECM algorithm for computationally efficient MAP estimation.
result PROBE algorithm provides robust and efficient coordinate-wise optimization.

This work defines idealized SSL representations and improves existing methods.

problem Unclear characteristics of SSL representations leading to high downstream accuracies.
method Characterized ideal properties and derived necessary and sufficient conditions.
result Improved SSL methods and derived new objectives for contrastive and non-contrastive learning.

The paper studies grid homology for spatial graphs and proves a Künneth formula for connected sums.

problem Understanding grid homology for spatial graphs with various types of edges.
method Developed grid homology for spatial graphs with cut edges and applied it to prove a Künneth formula for connected sums.
result A Künneth formula for knot Floer homology of connected sums is proven using grid homology.

Optimal self-distillation improves generative models' velocity risk and mode recovery.

problem Improving generative models' velocity risk and mode recovery.
method Proved optimal self-distillation for rectified flow via linear probing, derived mixing coefficient, and provided validation tuning.
result Optimal self-distillation improves velocity risk and mode recovery.