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48 results for Star Token

User surveys for Quality of Experience (QoE) are a critical source of information. In addition to the common "star rating" used to estimate Mean Opinion Score (MOS), more detailed survey questions (problem tokens) about specific areas provide valuable insight into the factors impacting QoE. This paper explores two aspe…

2018-08-19abs ↗pdf ↗

Fine-tuning improves information conveyance in language models by reorganizing uncertainty into more informative sequences.

problem Uncertainty reduction in large language models through fine-tuning is not fully understood, especially regarding output length.
method Proposed Canopy Entropy (CE\mathrm{CE}^\star) to measure uncertainty in both output length and sequence, capturing total Shannon entropy.
result Fine-tuned models exhibit stronger positive correlation between entropy rate and semantic diversity, indicating more informative and semantically meaningful generations.

Neural sequence generation is typically performed token-by-token and left-to-right. Whenever a token is generated only previously produced tokens are taken into consideration. In contrast, for problems such as sequence classification, bidirectional attention, which takes both past and future tokens into consideration, …

2019-08-16abs ↗pdf ↗

This research improves capital efficiency and impermanent loss in cryptocurrency markets using multi-token trading pools.

problem Poor impermanent loss and capital efficiency in automated market makers.
method Analysis and construction of a multi-token token proactive market maker (MPMM).
result MPMM shows better impermanent loss and capital efficiency than comparable market makers.

This study examines whether tokenized assets improve liquidity and finds significant differences across categories.

problem Improving liquidity for real-world assets through tokenization.
method Examined tokenized real-world assets using Ethereum-based data, measuring liquidity through turnover, active addresses, and active-month indicator.
result Gold-backed tokens show more persistent on-chain activity than Treasury and private-credit-related products, but asset value alone does not reliably predict liquidity.

Paper proves conjecture about star-shaped curves evolving under GAPF, but not always preserves star shape.

problem What conditions guarantee global existence of Gage's area-preserving flow for nonconvex initial curves?
method Using Dittberner's singularity analysis theory, constructed a ``flying wing'' curve to show limitations.
result Gage's area-preserving flow does not always preserve star-shapedness of evolving curves.

In this article, we introduce the notion of star-Ricci tensors in the real hypersurfaces of complex quadric QmQ^m. It is proved that there exist no Hopf hypersurfaces in Qm,m3Q^m,m\geq3, with commuting star-Ricci tensor or parallel star-Ricci tensor. As a generalization of star-Einstein metric, star-Ricci solitons on MM

2017-10-29abs ↗pdf ↗

Paper introduces a method to assess liquidity risk in meme tokens using entity-linked address analysis.

problem High market volatility and vulnerability to manipulation in meme tokens.
method Multi-dimensional approach integrating fund flow analysis, behavioral similarity, and anomalous transaction detection.
result Significant disparities between apparent and actual liquidity in meme token markets.

DOS improves language model generation by considering inter-token dependencies.

problem Lack of sequence-level information and inter-token dependencies in existing decoding strategies.
method Dependency-Oriented Sampler (DOS) that uses attention matrices to approximate inter-token dependencies.
result DOS consistently achieves superior performance on code generation and mathematical reasoning tasks.

New set-valued star-shaped risk measures introduced for better risk assessment.

problem Improving risk assessment in financial contexts.
method Developed new set-valued star-shaped risk measures and proved their representation theorems.
result Set-valued star-shaped risk measures can be represented as unions of set-valued convex risk measures.

The paper studies dynamic star-shaped risk measures and their representation.

problem Representing dynamic star-shaped risk measures and their properties.
method Representation theorems for dynamic monetary and star-shaped risk measures.
result Dynamic star-shaped risk measures can be represented as the lower envelope of a family of dynamic convex risk measures.

Proving that next-token prediction makes language models generate coherent long documents.

problem Understanding why language models generate coherent documents despite focusing on next-token prediction.
method Proving the power of next-token prediction in learning longer-range structure using Recurrent Neural Networks (RNN).
result Optimizing next-token prediction in RNNs yields a model that closely approximates the training distribution, even for long-range coherence.

The paper characterizes dynamic return and star-shaped risk measures via BSDEs.

problem Characterizing dynamic return and star-shaped risk measures.
method Characterization of star-shaped functionals and BSDEs.
result Existence of convex BSDEs with non-empty set of supersolutions.

Deform moment map on symplectic connections using star product algebras.

problem Understanding symplectic connections and their deformations.
method Study vector bundle of Fedosov star product algebras, formal connection, curvature, and star product trace.
result Showed star product trace as a formal symplectic form and moment map.

QA-Token improves tokenization for noisy data, boosting model performance.

problem Tokenization ignores data quality, limiting model effectiveness on noisy corpora.
method QA-Token combines signal quality with vocabulary construction through bilevel optimization and reinforcement learning.
result QA-Token achieves state-of-the-art performance on genomic and financial datasets.

Minimal token perturbations reveal how Transformer models process information.

problem Understanding information propagation in Transformer models for interpretability.
method Study of minimal token perturbations on embedding space.
result Rare tokens cause larger shifts, and input information mixes deeper.

LLM-as-a-service prices vary arbitrarily due to tokenization multiplicity.

problem Arbitrary price variation in LLM-as-a-service due to multiple tokenizations of the same output.
method Introduce canonical generation to restrict LLMs to unique tokenizations and develop an efficient sampling algorithm.
result Our sampling algorithm for canonical generation solves tokenization multiplicity and maintains comparable performance and runtime to standard sampling.

Paper analyzes Birkhoff relaxation for graph alignment, providing theoretical guarantees.

problem Finding vertex correspondence between two graphs to maximize edge overlap.
method Birkhoff relaxation as a convex relaxation of the quadratic assignment problem (QAP).
result Theoretical guarantees on the performance of Birkhoff relaxation under specific conditions.

New partition designs reduce star discrepancy in high-dimensional sampling.

problem Improving the expected star discrepancy in high-dimensional sampling.
method Developed non-equal volume partitions to achieve lower expected star discrepancy.
result Explicit upper bounds for expected star discrepancy under non-equal volume partitions.

New insights show stochastic initialization prevents token clustering in deep Transformers.

problem Understanding token dynamics in deep stochastic Transformers.
method Analysis of deep Transformers with random initialization noise, proving convergence to an interacting-particle system on the sphere.
result Initialization noise prevents token clustering, leading to antipodal formations.

We compare the star surgery operations introduced in [KS] to the generalized rational blow-down. We show that star surgery shares the properties that make rational blow-down useful for constructions of small exotic symplectic 4-manifolds. Then we show that star surgery operations provide a strictly more general class o…

2014-07-11abs ↗pdf ↗

The paper analyzes risk spillovers between AI ETFs, AI tokens, and green markets.

problem Risk spillovers among AI ETFs, AI tokens, and green markets.
method R2 decomposition method
result AI ETFs and clean energy act as risk transmitters, while AI tokens and green assets act as receivers.

We derive a closed formula for a star-product on complex projective space and on the domain SU(n+1)/S(U(1)×U(n))SU(n+1)/S(U(1)\times U(n)) using a completely elementary construction: Starting from the standard star-product of Wick type on Cn+1{0}C^{n+1} \setminus \{ 0 \} and performing a quantum analogue of Marsden-Weinstein reduction, we ca…

1995-03-09abs ↗pdf ↗

Estimates how many times a star appears due to gravitational lensing.

problem Estimating the number of times an observer sees a star due to gravitational lensing.
method Use affine linking numbers to estimate the number of times an observer sees a star.
result Estimates the number of times an observer sees a star due to gravitational lensing.

Study reveals risks of investing in new crypto-tokens in decentralized exchanges.

problem Risks associated with investing in newly created tokens in decentralized exchanges.
method Analysis of financial impact, market dynamics, profitability, and liquidity manipulations.
result Significant market liquidity trapped in honeypots, reducing market efficiency and misleading investors.

Tokenized RWAs face liquidity issues despite promising markets.

problem Low trading volumes and limited investor participation in tokenized assets.
method Empirical analysis of tokenized real estate, private credit, and treasury funds.
result Most tokenized assets exhibit low transfer activity and limited secondary trading.

Improved SGD learning for single index models reduces sample complexity.

problem Learning a single index model with optimal sample complexity.
method Using smoothed loss in online SGD to reduce sample complexity.
result Online SGD with smoothed loss achieves optimal sample complexity of dk/2d^{k^\star/2}.

Let KK be a nontrivial knot in S3S^{3} and t(K)t(K) its tunnel number. For any (p2,q)(p\geq 2,q)-slope in the torus boundary of a closed regular neighborhood of K K in S3S^{3}, denoted by KK^{\star}, it is a nontrivial cable knot in S3S^{3}. Though t(K)t(K)+1t(K^{\star})\leq t(K)+1, Example 1.1 in Section 1 shows that in some cas…

2020-02-18abs ↗pdf ↗

Fan tokens surged before World Cup matches, but declined during them, revealing cognitive biases.

problem Analyzing the impact of FIFA World Cup matches on fan tokens.
method Event study and intraday analysis of blockchain-based fan tokens.
result Fan tokens experienced a surge in returns six months before the World Cup, followed by a decline during the matches, revealing asymmetries in performance.

The paper finds at least four prime closed characteristics on star-shaped hypersurfaces in 8D space.

problem Finding prime closed characteristics on compact star-shaped hypersurfaces in 8D space.
method Proved existence of at least four prime closed characteristics for non-degenerate C3C^3 compact star-shaped hypersurfaces in R8\mathbb{R}^{8} without prime closed characteristics of Maslov-type index -1.
result Existence of at least four prime closed characteristics on compact star-shaped hypersurfaces in R8\mathbb{R}^{8}.

This paper connects monetary and star-shaped risk measures by showing their equivalence under certain conditions.

problem Understanding the relationship between monetary and star-shaped risk measures.
method Analyzing the acceptability of 0 and the normalization property.
result Monetary risk measures are only a translation away from star-shapedness under mild conditions.

Given a bordified space, Karlsson defines an incidence geometry of stars at infinity. These stars and their incidence are closely related to well-understood objects when the space is hyperbolic, CAT(0), or a bounded convex domain with the Hilbert metric. A question stemming from Karlsson's original paper was whether or…

2020-01-17abs ↗pdf ↗