Update citation and backend list (#342)

* Update citation and backend list

* Fix link

* Extrefs

Author: gdalle

CITATION.bib

@@ -0,0 +1,15 @@
+@software{Dalle_DifferentiationInterface_2024,
+  title  = {DifferentiationInterface.jl},
+  author = {Dalle, Guillaume and Hill, Adrian},
+  year   = 2024,
+  doi    = {10.5281/zenodo.11092033},
+  url    = {https://github.com/gdalle/DifferentiationInterface.jl}
+}
+
+@article{Schafer_AbstractDifferentiation_2021,
+  title   = {AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia},
+  author  = {Sch{\"a}fer, Frank and Tarek, Mohamed and White, Lyndon and Rackauckas, Chris},
+  journal = {NeurIPS 2021 Differentiable Programming Workshop},
+  year    = {2021},
+  url     = {https://github.com/JuliaDiff/AbstractDifferentiation.jl}
+}

CITATION.cff

@@ -86,7 +86,6 @@ value_and_gradient(f, AutoZygote(),      x) # returns (5.0, [2.0, 4.0]) with Zyg
 
 To improve your performance by up to several orders of magnitude compared to this example, take a look at the [DifferentiationInterface tutorial](https://gdalle.github.io/DifferentiationInterface.jl/DifferentiationInterface/stable/tutorial1/) and its section on operator preparation.
 
-## Related packages
+## Citation
 
-- [AbstractDifferentiation.jl](https://github.com/JuliaDiff/AbstractDifferentiation.jl) is the original inspiration for DifferentiationInterface.jl.
-- [AutoDiffOperators.jl](https://github.com/oschulz/AutoDiffOperators.jl) is an attempt to bridge ADTypes.jl with AbstractDifferentiation.jl.
+Please cite both DifferentiationInterface.jl and its inspiration [AbstractDifferentiation.jl](https://github.com/JuliaDiff/AbstractDifferentiation.jl), using the provided `CITATION.bib` file.

DifferentiationInterface/README.md

@@ -5,7 +5,37 @@ This page is about the latter, check out [that page](@ref "Operators") to learn
 
 ## List of backends
 
-We support all dense backend choices from [ADTypes.jl](https://github.com/SciML/ADTypes.jl), as well as their sparse wrapper [`AutoSparse`](@extref ADTypes.AutoSparse).
+We support all dense backend choices from [ADTypes.jl](https://github.com/SciML/ADTypes.jl):
+
+- [`AutoDiffractor`](@extref ADTypes.AutoDiffractor)
+- [`AutoEnzyme`](@extref ADTypes.AutoEnzyme)
+- [`AutoFastDifferentiation`](@extref ADTypes.AutoFastDifferentiation)
+- [`AutoFiniteDiff`](@extref ADTypes.AutoFiniteDiff)
+- [`AutoFiniteDifferences`](@extref ADTypes.AutoFiniteDifferences)
+- [`AutoForwardDiff`](@extref ADTypes.AutoForwardDiff)
+- [`AutoPolyesterForwardDiff`](@extref ADTypes.AutoPolyesterForwardDiff)
+- [`AutoReverseDiff`](@extref ADTypes.AutoReverseDiff)
+- [`AutoSymbolics`](@extref ADTypes.AutoSymbolics)
+- [`AutoTapir`](@extref ADTypes.AutoTapir)
+- [`AutoTracker`](@extref ADTypes.AutoTracker)
+- [`AutoZygote`](@extref ADTypes.AutoZygote)
+
+We also support the sparse wrapper [`AutoSparse`](@extref ADTypes.AutoSparse).
+
+## Compatibility
+
+DifferentiationInterface.jl itself is compatible with Julia 1.6, the Long Term Support (LTS) version of the language.
+However, we were only able to test the following backends on Julia 1.6:
+
+- `AutoFiniteDifferences`
+- `AutoForwardDiff`
+- `AutoReverseDiff`
+- `AutoTracker`
+- `AutoZygote`
+
+We strongly recommend that users upgrade to Julia 1.10 or above, where all backends are tested.
+
+## Features
 
 ```@setup backends
 using ADTypes
@@ -52,7 +82,7 @@ println(io, "| Backend | Availability | Two-argument functions | Hessian support
 println(io, "|:--------|:------------:|:----------------------:|:---------------:|")
 
 for b in backend_examples
-    join(io, ["[`$(nameof(typeof(b)))`](@extref ADTypes)", unicode_check_available(b), unicode_check_twoarg(b), unicode_check_hessian(b)], '|')
+    join(io, ["`$(nameof(typeof(b)))`", unicode_check_available(b), unicode_check_twoarg(b), unicode_check_hessian(b)], '|')
     println(io, '|' )
 end
 backend_table = Markdown.parse(String(take!(io)))
@@ -62,21 +92,6 @@ backend_table = Markdown.parse(String(take!(io)))
 backend_table #hide
 ```
 
-## Compatibility
-
-DifferentiationInterface.jl itself is compatible with Julia 1.6, the Long Term Support (LTS) version of the language.
-However, we were only able to test the following backends on Julia 1.6:
-
-- FiniteDifferences.jl
-- ForwardDiff.jl
-- ReverseDiff.jl
-- Tracker.jl
-- Zygote.jl
-
-We strongly recommend that users upgrade to Julia 1.10, where all backends are tested.
-
-## Checks
-
 ### Availability
 
 You can use [`check_available`](@ref) to verify whether a given backend is loaded.