108 research outputs found

    Evaluating statistical language models as pragmatic reasoners

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    The relationship between communicated language and intended meaning is often probabilistic and sensitive to context. Numerous strategies attempt to estimate such a mapping, often leveraging recursive Bayesian models of communication. In parallel, large language models (LLMs) have been increasingly applied to semantic parsing applications, tasked with inferring logical representations from natural language. While existing LLM explorations have been largely restricted to literal language use, in this work, we evaluate the capacity of LLMs to infer the meanings of pragmatic utterances. Specifically, we explore the case of threshold estimation on the gradable adjective ``strong'', contextually conditioned on a strength prior, then extended to composition with qualification, negation, polarity inversion, and class comparison. We find that LLMs can derive context-grounded, human-like distributions over the interpretations of several complex pragmatic utterances, yet struggle composing with negation. These results inform the inferential capacity of statistical language models, and their use in pragmatic and semantic parsing applications. All corresponding code is made publicly available (https://github.com/benlipkin/probsem/tree/CogSci2023).Comment: 8 pages, 4 figures, to appear in the Proceedings of the Annual Meeting of the Cognitive Science Society 202

    LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers

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    Logical reasoning, i.e., deductively inferring the truth value of a conclusion from a set of premises, is an important task for artificial intelligence with wide potential impacts on science, mathematics, and society. While many prompting-based strategies have been proposed to enable Large Language Models (LLMs) to do such reasoning more effectively, they still appear unsatisfactory, often failing in subtle and unpredictable ways. In this work, we investigate the validity of instead reformulating such tasks as modular neurosymbolic programming, which we call LINC: Logical Inference via Neurosymbolic Computation. In LINC, the LLM acts as a semantic parser, translating premises and conclusions from natural language to expressions in first-order logic. These expressions are then offloaded to an external theorem prover, which symbolically performs deductive inference. Leveraging this approach, we observe significant performance gains on FOLIO and a balanced subset of ProofWriter for three different models in nearly all experimental conditions we evaluate. On ProofWriter, augmenting the comparatively small open-source StarCoder+ (15.5B parameters) with LINC even outperforms GPT-3.5 and GPT-4 with Chain-of-Thought (CoT) prompting by an absolute 38% and 10%, respectively. When used with GPT-4, LINC scores 26% higher than CoT on ProofWriter while performing comparatively on FOLIO. Further analysis reveals that although both methods on average succeed roughly equally often on this dataset, they exhibit distinct and complementary failure modes. We thus provide promising evidence for how logical reasoning over natural language can be tackled through jointly leveraging LLMs alongside symbolic provers. All corresponding code is publicly available at https://github.com/benlipkin/lin

    Explanatory parent–child conversation predominates at an evolution exhibit

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    To investigate how parents support children's learning at an exhibit on evolution, the conversations of 12 families were recorded, transcribed, and coded (6,263 utterances). Children (mean age 9.6 years) and parents visited Explore Evolution, which conveyed current research about the evolution of seven organisms. Families were engaged with the exhibit, staying an average of 44 minutes. Parents' and children's explanatory, nonexplanatory, and evolutionary conversation was coded. Overall, substantive explanatory conversation occurred in 65% of parent utterances, whereas nonexplanatory conversation occurred in 21% of the utterances. We found substantial use of exhibit text by parents (12.9% of utterances) who read it aloud and reframed the text for their children. Parents also used evolutionary terms and evolutionary concepts (10.2%), showing that such an exhibit is a valuable way to introduce this difficult topic to elementary‐school–aged children. Parents' use of explanatory conversation positively related to their children's use of explanatory and evolutionary conversation, indicating that a dialogic interchange was occurring. Parents' attitudes toward the exhibit content, particularly the issue of human evolution, related to the museum experience. Overall, this analysis shows that parents and children are having nuanced discussions and illustrates the potential of informal experiences in supporting children's learning of a complex topic. © 2011 Wiley Periodicals, Inc. Sci Ed 95: 720–744, 2011Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87180/1/20433_ftp.pd

    Global Geometric Affinity for Revealing High Fidelity Protein Interaction Network

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    Protein-protein interaction (PPI) network analysis presents an essential role in understanding the functional relationship among proteins in a living biological system. Despite the success of current approaches for understanding the PPI network, the large fraction of missing and spurious PPIs and a low coverage of complete PPI network are the sources of major concern. In this paper, based on the diffusion process, we propose a new concept of global geometric affinity and an accompanying computational scheme to filter the uncertain PPIs, namely, reduce the spurious PPIs and recover the missing PPIs in the network. The main concept defines a diffusion process in which all proteins simultaneously participate to define a similarity metric (global geometric affinity (GGA)) to robustly reflect the internal connectivity among proteins. The robustness of the GGA is attributed to propagating the local connectivity to a global representation of similarity among proteins in a diffusion process. The propagation process is extremely fast as only simple matrix products are required in this computation process and thus our method is geared toward applications in high-throughput PPI networks. Furthermore, we proposed two new approaches that determine the optimal geometric scale of the PPI network and the optimal threshold for assigning the PPI from the GGA matrix. Our approach is tested with three protein-protein interaction networks and performs well with significant random noises of deletions and insertions in true PPIs. Our approach has the potential to benefit biological experiments, to better characterize network data sets, and to drive new discoveries

    Using diffusion distances for flexible molecular shape comparison

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    <p>Abstract</p> <p>Background</p> <p>Many molecules are flexible and undergo significant shape deformation as part of their function, and yet most existing molecular shape comparison (MSC) methods treat them as rigid bodies, which may lead to incorrect shape recognition.</p> <p>Results</p> <p>In this paper, we present a new shape descriptor, named Diffusion Distance Shape Descriptor (DDSD), for comparing 3D shapes of flexible molecules. The diffusion distance in our work is considered as an average length of paths connecting two landmark points on the molecular shape in a sense of inner distances. The diffusion distance is robust to flexible shape deformation, in particular to topological changes, and it reflects well the molecular structure and deformation without explicit decomposition. Our DDSD is stored as a histogram which is a probability distribution of diffusion distances between all sample point pairs on the molecular surface. Finally, the problem of flexible MSC is reduced to comparison of DDSD histograms.</p> <p>Conclusions</p> <p>We illustrate that DDSD is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. The presented algorithm is robust and does not require any prior knowledge of the flexible regions.</p

    A pair of TESS planets spanning the radius valley around the nearby mid-M dwarf LTT 3780

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    We present the confirmation of two new planets transiting the nearby mid-M dwarf LTT 3780 (TIC 36724087, TOI-732, V=13.07V=13.07, Ks=8.204K_s=8.204, RsR_s=0.374 R_{\odot}, MsM_s=0.401 M_{\odot}, d=22 pc). The two planet candidates are identified in a single TESS sector and are validated with reconnaissance spectroscopy, ground-based photometric follow-up, and high-resolution imaging. With measured orbital periods of Pb=0.77P_b=0.77 days, Pc=12.25P_c=12.25 days and sizes rp,b=1.33±0.07r_{p,b}=1.33\pm 0.07 R_{\oplus}, rp,c=2.30±0.16r_{p,c}=2.30\pm 0.16 R_{\oplus}, the two planets span the radius valley in period-radius space around low mass stars thus making the system a laboratory to test competing theories of the emergence of the radius valley in that stellar mass regime. By combining 63 precise radial-velocity measurements from HARPS and HARPS-N, we measure planet masses of mp,b=2.620.46+0.48m_{p,b}=2.62^{+0.48}_{-0.46} M_{\oplus} and mp,c=8.61.3+1.6m_{p,c}=8.6^{+1.6}_{-1.3} M_{\oplus}, which indicates that LTT 3780b has a bulk composition consistent with being Earth-like, while LTT 3780c likely hosts an extended H/He envelope. We show that the recovered planetary masses are consistent with predictions from both photoevaporation and from core-powered mass loss models. The brightness and small size of LTT 3780, along with the measured planetary parameters, render LTT 3780b and c as accessible targets for atmospheric characterization of planets within the same planetary system and spanning the radius valley.Comment: Accepted to AJ. 8 figures, 6 tables. CSV file of the RV measurements (i.e. Table 2) are included in the source cod

    Pacing and Decision Making in Sport and Exercise: The Roles of Perception and Action in the Regulation of Exercise Intensity

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    In pursuit of optimal performance, athletes and physical exercisers alike have to make decisions about how and when to invest their energy. The process of pacing has been associated with the goal-directed regulation of exercise intensity across an exercise bout. The current review explores divergent views on understanding underlying mechanisms of decision making in pacing. Current pacing literature provides a wide range of aspects that might be involved in the determination of an athlete's pacing strategy, but lacks in explaining how perception and action are coupled in establishing behaviour. In contrast, decision-making literature rooted in the understanding that perception and action are coupled provides refreshing perspectives on explaining the mechanisms that underlie natural interactive behaviour. Contrary to the assumption of behaviour that is managed by a higher-order governor that passively constructs internal representations of the world, an ecological approach is considered. According to this approach, knowledge is rooted in the direct experience of meaningful environmental objects and events in individual environmental processes. To assist a neuropsychological explanation of decision making in exercise regulation, the relevance of the affordance competition hypothesis is explored. By considering pacing as a behavioural expression of continuous decision making, new insights on underlying mechanisms in pacing and optimal performance can be developed. © 2014 Springer International Publishing Switzerland

    The L 98-59 System: Three Transiting, Terrestrial-size Planets Orbiting a Nearby M Dwarf

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    We report the Transiting Exoplanet Survey Satellite (TESS) discovery of three terrestrial-size planets transiting L 98-59 (TOI-175, TIC 307210830)—a bright M dwarf at a distance of 10.6 pc. Using the Gaia-measured distance and broadband photometry, we find that the host star is an M3 dwarf. Combined with the TESS transits from three sectors, the corresponding stellar parameters yield planet radii ranging from 0.8 R ⊕ to 1.6 R ⊕. All three planets have short orbital periods, ranging from 2.25 to 7.45 days with the outer pair just wide of a 2:1 period resonance. Diagnostic tests produced by the TESS Data Validation Report and the vetting package DAVE rule out common false-positive sources. These analyses, along with dedicated follow-up and the multiplicity of the system, lend confidence that the observed signals are caused by planets transiting L 98-59 and are not associated with other sources in the field. The L 98-59 system is interesting for a number of reasons: the host star is bright (V = 11.7 mag, K = 7.1 mag) and the planets are prime targets for further follow-up observations including precision radial-velocity mass measurements and future transit spectroscopy with the James Webb Space Telescope; the near-resonant configuration makes the system a laboratory to study planetary system dynamical evolution; and three planets of relatively similar size in the same system present an opportunity to study terrestrial planets where other variables (age, metallicity, etc.) can be held constant. L 98-59 will be observed in four more TESS sectors, which will provide a wealth of information on the three currently known planets and have the potential to reveal additional planets in the system
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