Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Chain-of-Thought (CoT) prompting can dramatically improve the multi-step reasoning abilities of large language models (LLMs). CoT explicitly encourages the LLM to generate intermediate rationales for solving a problem, by providing a series of reasoning steps in the demonstrations. Despite its success, there is still little understanding of what makes CoT prompting effective and which aspects of the demonstrated reasoning steps contribute to its performance. In this paper, we show that CoT reasoning is possible even with invalid demonstrations - prompting with invalid reasoning steps can achieve over 80-90% of the performance obtained using CoT under various metrics, while still generating coherent lines of reasoning during inference. Further experiments show that other aspects of the rationales, such as being relevant to the query and correctly ordering the reasoning steps, are much more important for effective CoT reasoning. Overall, these findings both deepen our understanding of CoT prompting, and open up new questions regarding LLMs' capability to learn to reason in context.Comment: ACL-23 Camera Ready. Code and model input/output are available at https://github.com/sunlab-osu/Understanding-Co

Solving Robotic Trajectory Sequential Writing Problem via Learning Character’s Structural and Sequential Information

The writing sequence of numerals or letters often affects aesthetic aspects of the writing outcomes. As such, it remains a challenge for robotic calligraphy systems to perform, mimicking human writers’ implicit intention. This article presents a new robot calligraphy system that is able to learn writing sequences with limited sequential information, producing writing results compatible to human writers with good diversity. In particular, the system innovatively applies a gated recurrent unit (GRU) network to generate robotic writing actions with the support of a prelabeled trajectory sequence vector. Also, a new evaluation method is proposed that considers the shape, trajectory sequence, and structural information of the writing outcome, thereby helping ensure the writing quality. A swarm optimization algorithm is exploited to create an optimal set of parameters of the proposed system. The proposed approach is evaluated using Arabic numerals, and the experimental results demonstrate the competitive writing performance of the system against state-of-the-art approaches regarding multiple criteria (including FID, MAE, PSNR, SSIM, and PerLoss), as well as diversity performance concerning variance and entropy. Importantly, the proposed GRU-based robotic motion planning system, supported with swarm optimization can learn from a small dataset, while producing calligraphy writing with diverse and aesthetically pleasing outcomes

Burst expansion, distribution and diversification of MITEs in the silkworm genome

<p>Abstract</p> <p>Background</p> <p>Miniature inverted-repeat transposable elements (MITEs) are widespread in plants and animals. Although silkworm (<it>Bombyx mori</it>) has a large amount of and a variety of transposable elements, the genome-wide information of the silkworm MITEs is unknown.</p> <p>Results</p> <p>We used structure-based and homology approaches to search for MITEs in the silkworm genome. We identified 17 MITE families with a total of 5785 members, accounting for ~0.4% of the genome. 7 of 17 MITE families are completely novel based on the nucleotide composition of target site duplication (TSD) and/or terminal inverted repeats (TIR). Silkworm MITEs were widely and nonrandom distributed in the genome. One family named BmMITE-2 might experience a recent burst expansion. Network and diversity analyses for each family revealed different diversification patterns of the silkworm MITEs, reflecting the signatures of genome-shocks that silkworm experienced. Most silkworm MITEs preferentially inserted into or near genes and BmMITE-11 that encodes a germline-restricted small RNA might silence its the closest genes in silkworm ovary through a small RNA pathway.</p> <p>Conclusions</p> <p>Silkworm harbors 17 MITE families. The silkworm MITEs preferred to reside in or near genes and one MITE might be involved in gene silence. Our results emphasize the exceptional role of MITEs in transcriptional regulation of genes and have general implications to understand interaction between MITEs and their host genome.</p

Visual-Guided Robotic Object Grasping Using Dual Neural Network Controllers

It has been a challenging task for a robotic arm to accurately reach and grasp objects, which has drawn much research attention. This article proposes a robotic hand–eye coordination system by simulating the human behavior pattern to achieve a fast and robust reaching ability. This is achieved by two neural-network-based controllers, including a rough reaching movement controller implemented by a pretrained radial basis function for rough reaching movements, and a correction movement controller built from a specifically designed brain emotional nesting network (BENN) for smooth correction movements. In particular, the proposed BENN is designed with high nonlinear mapping ability, with its adaptive laws derived from the Lyapunov stability theorem; from this, the robust tracking performance and accordingly the stability of the proposed control system are guaranteed by the utilization of the H∞ control approach. The proposed BENN is validated and evaluated by a chaos synchronization simulation, and the overall control system by object grasping tasks through a physical robotic arm in a real-world environment. The experimental results demonstrate the superiority of the proposed control system in reference to those with single neural networks

A Developmental Evolutionary Learning Framework for Robotic Chinese Stroke Writing

The ability of robots to write Chinese strokes, which is recognized as a sophisticated task, involves complicated kinematic control algorithms. The conventional approaches for robotic writing of Chinese strokes often suffer from limited font generation methods, which limits the ability of robots to perform high-quality writing. This paper instead proposes a developmental evolutionary learning framework that enables a robot to learn to write fundamental Chinese strokes. The framework first considers the learning process of robotic writing as an evolutionary easy-to-difficult procedure. Then, a developmental learning mechanism called &#x201C;Lift-constraint, act and saturate&#x201D; that stems from developmental robotics is used to determine how the robot learns tasks ranging from simple to difficult by building on the learning results from the easy tasks. The developmental constraints, which include altitude adjustments, number of mutation points, and stroke trajectory points, determine the learning complexity of robot writing. The developmental algorithm divides the evolutionary procedure into three developmental learning stages. In each stage, the stroke trajectory points gradually increase, while the number of mutation points and adjustment altitudes gradually decrease, allowing the learning difficulties involved in these three stages to be categorized as easy, medium, and difficult. Our robot starts with an easy learning task and then gradually progresses to the medium and difficult tasks. Under various developmental constraint setups in each stage, the robot applies an evolutionary algorithm to handle the basic shapes of the Chinese strokes and eventually acquires the ability to write with good quality. The experimental results demonstrate that the proposed framework allows a calligraphic robot to gradually learn to write five fundamental Chinese strokes and also reveal a developmental pattern similar to that of humans. Compared to an evolutionary algorithm without the developmental mechanism, the proposed framework achieves good writing quality more rapidly

MiR–20a-5p promotes radio-resistance by targeting Rab27B in nasopharyngeal cancer cells

Additional file 3: Figure S2. The protein level of PARP and caspase3 detected by western in NCM, 5PM, NCA, 5PA, si-NC and si-Rab27B transfected CNE-2 and CNE-1 cells respectively

Panorama phylogenetic diversity and distribution of type A influenza viruses based on their six internal gene sequences

<p>Abstract</p> <p>Background</p> <p>Type A influenza viruses are important pathogens of humans, birds, pigs, horses and some marine mammals. The viruses have evolved into multiple complicated subtypes, lineages and sublineages. Recently, the phylogenetic diversity of type A influenza viruses from a whole view has been described based on the viral external HA and NA gene sequences, but remains unclear in terms of their six internal genes (PB2, PB1, PA, NP, MP and NS).</p> <p>Methods</p> <p>In this report, 2798 representative sequences of the six viral internal genes were selected from GenBank using the web servers in NCBI Influenza Virus Resource. Then, the phylogenetic relationships among the representative sequences were calculated using the software tools MEGA 4.1 and RAxML 7.0.4. Lineages and sublineages were classified mainly according to topology of the phylogenetic trees and distribution of the viruses in hosts, regions and time.</p> <p>Results</p> <p>The panorama phylogenetic trees of the six internal genes of type A influenza viruses were constructed. Lineages and sublineages within the type based on the six internal genes were classified and designated by a tentative universal numerical nomenclature system. The diversity of influenza viruses circulating in different regions, periods, and hosts based on the panorama trees was analyzed.</p> <p>Conclusion</p> <p>This study presents the first whole views to the phylogenetic diversity and distribution of type A influenza viruses based on their six internal genes. It also proposes a tentative universal nomenclature system for the viral lineages and sublineages. These can be a candidate framework to generalize the history and explore the future of the viruses, and will facilitate future scientific communications on the phylogenetic diversity and evolution of the viruses. In addition, it provides a novel phylogenetic view (i.e. the whole view) to recognize the viruses including the origin of the pandemic A(H1N1) influenza viruses.</p

Summary of 615 patients of chronic myeloid leukemia in Shanghai from 2001 to 2006

<p>Abstract</p> <p>Background</p> <p>To retrospectively review the incidence, treatment efficacy, we followed up newly diagnosed chronic myelogenous leukemia (CML) patients residing in Shanghai during 2001-2006.</p> <p>Methods</p> <p>All eligible cases were reviewed with the data of efficacy responses as well as overall survival (OS) and progression-free survival (PFS) time.</p> <p>Results</p> <p>A total of 615 cases entered the study. CML mainly afflicted those aged 40-60 years old and was slightly more frequent in males than females. More than 85% of the patients were in chronic phase (CP) when diagnosed. All patients were divided into four groups based on the main regimens - hydroxyurea, interferon alpha (IFN-α), imatinib, and hemopoietic stem cell transplantation (HSCT). With the median follow-up of 18 months, imatinib treatment induced 92.2% complete hematologic responses, and 64.3% complete cytogenetic responses among CML-CP patients. Overall the therapeutic efficacy in the imatinib group was higher than that in the hydroxyurea or IFN-α group. Meanwhile, in the imatinib group, all response rates of patients in CP were significantly greater than that in accelerated or blastic crisis phase. The patients treated with imatinib also showed the most promising results regarding OS and PFS. Patients receiving HSCT decreased markedly in number with the introduction of imatinib.</p> <p>Conclusions</p> <p>The number of new patients arising in Shanghai increased from 2001 to 2006. There were still patients receiving hydroxyurea and IFN-α. As the first-line regime for CML, imatinib was less administered in Shanghai before, but has received considerable development and great responses since 2003.</p