1-86 of about 86 matches for site:arxiv.org explain
[2209.09513] Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answerin
https://arxiv.org/abs/2209.09513
2209.09513] Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering Skip to
[2209.09513] Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answerin
https://arxiv.org/abs/2209.09513
2209.09513] Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering Skip to
[2307.08678] Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explana
https://arxiv.org/abs/2307.08678
2307.08678] Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations Skip to main content We
https://arxiv.org/abs/2406.06527
attempt to disentangle the object geometry, materials, and lighting that explain the input
https://arxiv.org/abs/2207.00026
universally applied. 2) Statistically grounded: We provide a detailed analysis to theoretically explain the applicability
https://arxiv.org/abs/2207.00026
universally applied. 2) Statistically grounded: We provide a detailed analysis to theoretically explain the applicability
https://arxiv.org/abs/2112.08674
of generating fluent-appearing text with relatively little task-specific supervision. But can these models accurately explain classification decisions? We consider
https://arxiv.org/abs/2507.06187
of each individual data point. We formulate the delta learning hypothesis to explain this phenomenon, positing that
https://arxiv.org/abs/2507.06187
of each individual data point. We formulate the delta learning hypothesis to explain this phenomenon, positing that
https://arxiv.org/abs/2303.01471
to 75 dimensions. Finally, we propose a "three-phase picture" to explain the behavior
https://arxiv.org/abs/2302.10329
human control. Our work explores increasingly agentic algorithmic systems in three parts. First, we explain the notion
https://arxiv.org/abs/2303.01471
to 75 dimensions. Finally, we propose a "three-phase picture" to explain the behavior
https://arxiv.org/abs/2410.04642
rate $\eta$, identifying several scaling regimes in the $\gamma$-$\eta$ plane which we explain theoretically using a
https://arxiv.org/abs/2410.04642
rate $\eta$, identifying several scaling regimes in the $\gamma$-$\eta$ plane which we explain theoretically using a
[1211.5555] Toward a Comprehensive Model of Snow Crystal Growth Dynamics: 1. Overarching Features an
http://arxiv.org/abs/1211.5555
plates and hollow columnar forms. Putting these elements together, we are able to explain the overall
https://arxiv.org/abs/2502.15657
and safe by design, which we call Scientist AI. This system is designed to explain the world
https://arxiv.org/abs/1501.00011
is, and what we can learn from it. Comments: 6 pages, written to explain quantum computing to
https://arxiv.org/abs/1201.2759
has suggested to many that its ingredients are all one needs to explain galaxies and their
https://arxiv.org/abs/hep-th/9111043
to Lie-bi algebras and the classical Yang-Baxter equation. Then we explain in detail
https://arxiv.org/abs/2311.00078
is currently no agreed upon set of parameters which is able to explain all of the
https://arxiv.org/abs/1102.2331
of gene birth (duplication and transfer) and death (loss) to explain the evolution
https://arxiv.org/abs/hep-th/0203101
relevant spacetime regions to any given surface, is discussed in detail. We explain how the bound
https://arxiv.org/abs/2009.06499
equilibrium processes. None of these potential phosphine production pathways are sufficient to explain the presence
[2008.03534] A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Pro
https://arxiv.org/abs/2008.03534
a subspace of the original input space that is sufficient to explain the output
http://arxiv.org/abs/math/0307200
group" of a space and various Lie 2-groups. We also explain how coherent 2-groups
[gr-qc/9211028] Thawing the Frozen Formalism: The Difference Between Observables and What We Observe
http://arxiv.org/abs/gr-qc/9211028
Hamiltonian. The problem of the frozen formalism is to explain how dynamics is possible
https://arxiv.org/abs/2009.00133
establish the contact prediction through unsupervised graphical models with topology constraints. Further, I will explain how to use
http://arxiv.org/abs/hep-th/9305026
Theory: An Introduction, by B. Zwiebach View PDF Abstract: In these introductory notes I explain some basic ideas in
http://arxiv.org/abs/gr-qc/9301017
has to appeal to the Weak Anthropic Principle to explain why we observe the
http://arxiv.org/abs/1504.02165v1
angle. Radio emission escaping from microwave ovens during the magnetron shut-down phase neatly explain all of the
http://arxiv.org/abs/gr-qc/9310022
A particular concern is the question whether it is possible to explain why entropy is low
https://arxiv.org/abs/1901.01417
structure of these posets when $\lambda$ has only one or two distinct parts. Finally, we explain how this work relates
https://arxiv.org/abs/2106.10165
relevance. Beginning from a first-principles component-level picture of networks, we explain how to determine
https://arxiv.org/abs/2303.13375
case study that shows the ability of GPT-4 to explain medical reasoning, personalize explanations
https://arxiv.org/abs/2501.04641
pre-training framework remains limited. This paper develops a theoretical framework to explain the success
https://arxiv.org/abs/2305.15324
to capabilities that pose extreme risks, such as offensive cyber capabilities or strong manipulation skills. We explain why model evaluation is
https://arxiv.org/abs/1704.05473
we describe the development of the new site and explain some of the
https://arxiv.org/abs/1704.05473
we describe the development of the new site and explain some of the
http://arxiv.org/abs/1501.00011
is, and what we can learn from it. Comments: 6 pages, written to explain quantum computing to
https://arxiv.org/abs/2304.11119
RCS algorithm we demonstrate experimentally that there are two phase transitions observable with XEB, which we explain theoretically with a
[2211.00593] Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 sma
https://arxiv.org/abs/2211.00593
3 other authors View PDF Abstract: Research in mechanistic interpretability seeks to explain behaviors of machine
https://arxiv.org/abs/2402.03239
the architecture of Bluesky and the AT Protocol, and explain how the technical
https://arxiv.org/abs/2303.17564
models on financial tasks by significant margins without sacrificing performance on general LLM benchmarks. Additionally, we explain our modeling choices, training
https://arxiv.org/abs/2105.01999
Energy landscapes summarize all possible dynamics of some physical systems. Energy(-like) landscapes can explain some biomolecular processes, including
https://arxiv.org/abs/2012.05770
Suvrat Raju View PDF Abstract: We review recent progress on the information paradox. We explain why exponentially small correlations
https://arxiv.org/abs/2009.04471
with simulations or incorrect assumptions about the properties of dark matter could explain our results. Comments: 56
https://arxiv.org/abs/2303.13375
case study that shows the ability of GPT-4 to explain medical reasoning, personalize explanations
[2211.00593] Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 sma
https://arxiv.org/abs/2211.00593
3 other authors View PDF Abstract: Research in mechanistic interpretability seeks to explain behaviors of machine
http://arxiv.org/abs/1503.05884
the ambient space, the statement is uniform in all parameters. We explain how this implies certain
http://arxiv.org/abs/1608.07236
mathcal{R}$ should act on the homology of an arithmetic group. We explain how the Taylor
https://arxiv.org/abs/1906.08649
of-the-art algorithms, such as PETS, TD3 and SAC. To explain the effectiveness
https://arxiv.org/abs/1709.07504
instances of the same reciprocity theorem for generalized permutahedra. 3. We explain why the formulas
https://arxiv.org/abs/2010.10325
R}$-motivic spectra, by Robert Burklund and 2 other authors View PDF Abstract: We explain how to reconstruct
https://arxiv.org/abs/2202.01771
gathering further improves combinatorial generalization, outperforming the best baseline by 25.1%. Finally, we explain these results by investigating
https://arxiv.org/abs/1602.01013
of information about users, content, and past performance, our best performing models can explain less than half of
https://arxiv.org/abs/2010.10325
R}$-motivic spectra, by Robert Burklund and 2 other authors View PDF Abstract: We explain how to reconstruct
https://arxiv.org/abs/2307.05691
a delayed process contribution. We find that KPM with $K=2$ is able to explain the abundances
https://arxiv.org/abs/2305.08955
and problems arising from multiple nested coercions related to number fields. We also explain how we integrated our
https://arxiv.org/abs/2105.01999
Energy landscapes summarize all possible dynamics of some physical systems. Energy(-like) landscapes can explain some biomolecular processes, including
[1503.02110] Chemical Cartography with APOGEE: Metallicity Distribution Functions and the Chemical S
http://arxiv.org/abs/1503.02110
that blurring of stellar populations by orbital eccentricities is not enough to explain the reversal
https://arxiv.org/abs/2303.17564
models on financial tasks by significant margins without sacrificing performance on general LLM benchmarks. Additionally, we explain our modeling choices, training
https://arxiv.org/abs/1911.01238
in physics, or of vanishing homology in mathematics. These notes will explain this relationship, and
https://arxiv.org/abs/2402.19415
this knowledge, summarize how cuts are used in various computational strategies, and explain their relations to
https://arxiv.org/abs/1602.01013
of information about users, content, and past performance, our best performing models can explain less than half of
[1809.06389] Spin Evolution and Cometary Interpretation of the Interstellar Minor Object 1I/2017 'Ou
https://arxiv.org/abs/1809.06389
the classification of 'Oumuamua as a comet (invoked to explain its claimed anomalous acceleration
https://arxiv.org/abs/1512.04993
patch). We provide calculations for the results quoted in that paper, explain how it fits into
https://arxiv.org/abs/2202.01771
gathering further improves combinatorial generalization, outperforming the best baseline by 25.1%. Finally, we explain these results by investigating
https://arxiv.org/abs/1906.08649
of-the-art algorithms, such as PETS, TD3 and SAC. To explain the effectiveness
https://arxiv.org/abs/2007.06061
also be used to distinguish among the models proposed to explain the current
https://arxiv.org/abs/1001.3080
properly understand these concepts. Thus the paper is organized aorund interpretations, conceptual pictures that explain the peculiar
https://arxiv.org/abs/2204.01182
the information gap theory and compression progress theory, have sought to explain how we engage in
https://arxiv.org/abs/2110.07783
it must make a suspiciously precise assumption in order to explain a certain
https://arxiv.org/abs/2405.00836
confidence. We show this preference for negative masses makes it challenging to explain the result
https://arxiv.org/abs/2010.07446
View PDF Abstract: The purpose of this work is to explain how wings work and
https://arxiv.org/abs/1804.03719
terms of qubit count, quality, and connectivity. This review aims to explain the principles
https://arxiv.org/html/2404.14219v1
par with models such as Mixtral 8x7B [ JSR + 24 ] and GPT-3.5. User: Explain why it is surprising
https://arxiv.org/abs/1205.4788
of dynamical systems having continuous dynamics described by various forms of differential equations. We explain the dynamical
https://arxiv.org/abs/1212.5608
Page View PDF Abstract: Science looks for the simplest hypotheses to explain observations. Starting with the
https://arxiv.org/abs/1205.4788
of dynamical systems having continuous dynamics described by various forms of differential equations. We explain the dynamical
https://arxiv.org/html/1709.00645
provide an introduction to this topic by explaining kernel-based inversion techniques. Specifically, we explain how various kernels are
https://arxiv.org/list/hep-ex/new
The existence of an eV-scale sterile neutrino has been proposed to explain several anomalous experimental results
https://arxiv.org/list/hep-ph/new
component that contributes to the DM curvature perturbation. In particular, we explain that an unperturbed axion