Avoiding Echo-Responses in a Retrieval-Based Conversation System

Retrieval-based conversation systems generally tend to highly rank responses that are semantically similar or even identical to the given conversation context. While the system's goal is to find the most appropriate response, rather than the most semantically similar one, this tendency results in low-quality responses. We refer to this challenge as the echoing problem. To mitigate this problem, we utilize a hard negative mining approach at the training stage. The evaluation shows that the resulting model reduces echoing and achieves better results in terms of Average Precision and Recall@N metrics, compared to the models trained without the proposed approach

Local ancestry prediction with PyLAE

We developed PyLAE, a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimating many parameters, it can process thousands of genomes within a day. PyLAE can run on phased or unphased genomic data. We have shown how PyLAE can be applied to the identification of differentially enriched pathways between populations. The local ancestry approach results in higher enrichment scores compared to whole-genome approaches. We benchmarked PyLAE using the 1000 Genomes dataset, comparing the aggregated predictions with the global admixture results and the current gold standard program RFMix. Computational efficiency, minimal requirements for data pre-processing, straightforward presentation of results, and ease of installation make PyLAE a valuable tool to study admixed populations

aqlaboratory/openfold: OpenFold v1.0.1

OpenFold as of the release of our manuscript. Many new features, including FP16 training + more stable training. What's Changed use multiple models for inference by @decarboxy in https://github.com/aqlaboratory/openfold/pull/117 Update input processing by @brianloyal in https://github.com/aqlaboratory/openfold/pull/116 adding a caption to the image in the readme by @decarboxy in https://github.com/aqlaboratory/openfold/pull/133 Properly handling file outputs when multiple models are evaluated by @decarboxy in https://github.com/aqlaboratory/openfold/pull/142 Fix for issue in download_mgnify.sh by @josemduarte in https://github.com/aqlaboratory/openfold/pull/166 Fix tag-sequence mismatch when predicting for multiple fastas by @sdvillal in https://github.com/aqlaboratory/openfold/pull/164 Support openmm >= 7.6 by @sdvillal in https://github.com/aqlaboratory/openfold/pull/163 Fixing issue in download_uniref90.sh by @josemduarte in https://github.com/aqlaboratory/openfold/pull/171 Fix propagation of use_flash for offloaded inference by @epenning in https://github.com/aqlaboratory/openfold/pull/178 Update deepspeed version to 0.5.10 by @NZ99 in https://github.com/aqlaboratory/openfold/pull/185 Fixes errors when processing .pdb files by @NZ99 in https://github.com/aqlaboratory/openfold/pull/188 fix incorrect learning rate warm-up after restarting from ckpt by @Zhang690683220 in https://github.com/aqlaboratory/openfold/pull/182 Add opencontainers image-spec to Dockerfile by @SauravMaheshkar in https://github.com/aqlaboratory/openfold/pull/128 Write inference and relaxation timings to a file by @brianloyal in https://github.com/aqlaboratory/openfold/pull/201 Minor fixes in setup scripts by @timodonnell in https://github.com/aqlaboratory/openfold/pull/202 Minor optimizations & fixes to support ESMFold by @nikitos9000 in https://github.com/aqlaboratory/openfold/pull/199 Drop chains that are missing (structure) data in training by @timodonnell in https://github.com/aqlaboratory/openfold/pull/210 adding a script for threading a sequence onto a structure by @decarboxy in https://github.com/aqlaboratory/openfold/pull/206 Set pin_memory to True in default dataloader config. by @NZ99 in https://github.com/aqlaboratory/openfold/pull/212 Fix missing subtract_plddt argument in prep_output call by @mhrmsn in https://github.com/aqlaboratory/openfold/pull/217 fp16 fixes by @beiwang2003 in https://github.com/aqlaboratory/openfold/pull/222 Set clamped vs unclamped FAPE for each sample in batch independently by @ar-nowaczynski in https://github.com/aqlaboratory/openfold/pull/223 Fix probabilities type (int -> float) by @atgctg in https://github.com/aqlaboratory/openfold/pull/225 Small fix for prep_mmseqs_dbs. by @jonathanking in https://github.com/aqlaboratory/openfold/pull/232 New Contributors @brianloyal made their first contribution in https://github.com/aqlaboratory/openfold/pull/116 @josemduarte made their first contribution in https://github.com/aqlaboratory/openfold/pull/166 @sdvillal made their first contribution in https://github.com/aqlaboratory/openfold/pull/164 @epenning made their first contribution in https://github.com/aqlaboratory/openfold/pull/178 @NZ99 made their first contribution in https://github.com/aqlaboratory/openfold/pull/185 @Zhang690683220 made their first contribution in https://github.com/aqlaboratory/openfold/pull/182 @SauravMaheshkar made their first contribution in https://github.com/aqlaboratory/openfold/pull/128 @timodonnell made their first contribution in https://github.com/aqlaboratory/openfold/pull/202 @nikitos9000 made their first contribution in https://github.com/aqlaboratory/openfold/pull/199 @mhrmsn made their first contribution in https://github.com/aqlaboratory/openfold/pull/217 @beiwang2003 made their first contribution in https://github.com/aqlaboratory/openfold/pull/222 @ar-nowaczynski made their first contribution in https://github.com/aqlaboratory/openfold/pull/223 @atgctg made their first contribution in https://github.com/aqlaboratory/openfold/pull/225 @jonathanking made their first contribution in https://github.com/aqlaboratory/openfold/pull/232 Full Changelog: https://github.com/aqlaboratory/openfold/compare/v1.0.0...v1.0.